modelId
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122
| author
stringlengths 2
42
⌀ | last_modified
timestamp[us, tz=UTC] | downloads
int64 0
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⌀ | tags
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kaengpil/jurin
|
kaengpil
| 2023-12-14T10:48:55Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-14T10:48:32Z |
---
license: openrail
---
|
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ADISH007/Aws_donut_10k_incremental_1_Epoch_18
|
ADISH007
| 2023-12-14T10:49:34Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"vision-encoder-decoder",
"endpoints_compatible",
"region:us"
] | null | 2023-12-14T10:49:16Z |
Entry not found
|
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peterholdsworth/andlogo
|
peterholdsworth
| 2023-12-14T10:49:42Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T10:49:42Z |
Entry not found
|
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mokkaraveendra/sdfsdfsdfsdfsf
|
mokkaraveendra
| 2023-12-14T10:49:45Z | 0 | 0 | null |
[
"license:openrail",
"region:us"
] | null | 2023-12-14T10:49:45Z |
---
license: openrail
---
|
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EmmaGthn/results_prefix_1_2000_moji
|
EmmaGthn
| 2023-12-14T13:59:50Z | 0 | 0 | null |
[
"tensorboard",
"safetensors",
"region:us"
] | null | 2023-12-14T10:50:57Z |
Entry not found
|
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] |
aaa12963337/msi-nat-mini-pretrain
|
aaa12963337
| 2023-12-16T07:12:44Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"nat",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:shi-labs/nat-mini-in1k-224",
"license:mit",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-14T10:51:48Z |
---
license: mit
base_model: shi-labs/nat-mini-in1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: msi-nat-mini-pretrain
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8727019498607242
---
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# msi-nat-mini-pretrain
This model is a fine-tuned version of [shi-labs/nat-mini-in1k-224](https://huggingface.co/shi-labs/nat-mini-in1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7304
- Accuracy: 0.8727
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1019 | 1.0 | 1562 | 0.3526 | 0.8976 |
| 0.0679 | 2.0 | 3125 | 0.6288 | 0.8837 |
| 0.0461 | 3.0 | 4686 | 0.7304 | 0.8727 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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mokkaraveendra/gdfgfdgfgg
|
mokkaraveendra
| 2023-12-14T11:08:52Z | 0 | 0 | null |
[
"arxiv:1910.09700",
"license:mit",
"region:us"
] | null | 2023-12-14T10:52:21Z |
---
license: mit
---
# Model Card for Model ID
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|
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Justice0893/T5_opus_en_tr_model
|
Justice0893
| 2023-12-14T10:52:29Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T10:52:28Z |
Entry not found
|
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Robertmaioe/KellyClarksonWeight
|
Robertmaioe
| 2023-12-14T10:56:45Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T10:54:36Z |
---
license: apache-2.0
---
➥✅ Official Website: Kelly Clarkson Weight Loss Dr OZ
➥✅ Product Name: Kelly Clarkson Weight Loss Dr OZ
➥✅ Benefits: Kelly Clarkson Weight Loss Dr OZ
of chronic pain & aches.
➥✅ Category: Pain Relief Supplement
➥✅ Rating: ★★★★☆ (4.5/5.0)
➥✅ Side Effects: No Major Side Effects
➥✅ Availability: In Stock Voted #1 Product in the USA
Kelly Clarkson, the powerhouse vocalist and beloved talk show host, has not only graced us with her incredible talent but has also become an inspiring beacon of wellness. Central to her transformative journey has been the guidance of Dr. Mehmet Oz, a prominent figure in health and wellness.
BLOGS:-
https://groups.google.com/a/chromium.org/g/chromium-reviews/c/3Kq3t4IBvqU
https://groups.google.com/a/chromium.org/g/chromium-reviews/c/g2aw40f0Me8
https://groups.google.com/a/chromium.org/g/chromium-reviews/c/24i2BaSc9Vs
https://groups.google.com/a/chromium.org/g/chromium-reviews/c/m-AgnqP6tjM
https://groups.google.com/a/chromium.org/g/chromium-reviews/c/ixNys28rk2o
https://groups.google.com/g/comp.os.vms/c/BLkjTOueU40
https://groups.google.com/g/mozilla.dev.platform/c/HUGUfIBt5FM
https://groups.google.com/g/kelly-clarkson-weight-loss-dr-oz-buy
https://groups.google.com/g/kelly-clarkson-weight-loss-dr-oz
https://sites.google.com/view/kellyclarksonweightlossdroz/
https://sites.google.com/view/kellyclarksonweightlossdrozbuy/
https://kellyclarksonweightlossdroz.company.site/
https://medium.com/@bobbycjoyce/kelly-clarkson-weight-loss-dr-oz-fake-or-legit-warning-dont-buy-until-you-read-this-ab6dbbb96f33
https://medium.com/@bobbycjoyce/kelly-clarkson-weight-loss-dr-oz-fake-or-legit-beware-shocking-fake-ads-0c26a1ee5a67
https://gamma.app/public/Kelly-Clarkson-Weight-Loss-DR-OZ--Ingredients-Side-Effects-Review-69r5exd2cfxac41
https://gamma.app/public/Kelly-Clarkson-Weight-Loss-DR-OZ-100-safe-Does-it-really-work-or--dhbkqh1vmmvm7kn
https://groups.google.com/g/kelly-clarkson-weight-loss-dr-oz-buy/c/ymw2YkRScnI
https://groups.google.com/g/kelly-clarkson-weight-loss-dr-oz/c/aABBIKkpe_Q
https://www.facebook.com/KellyClarksonWeightLossDrOZ/
https://www.facebook.com/Kelly.Clarkson.Keto.Blast.Gummies.Official/
https://www.facebook.com/kellyclarksonweightlossgummies/
https://www.facebook.com/KellyClarksonSlimFusionGummies/
https://www.facebook.com/KellyClarksonKetoFusionGummies/
https://www.facebook.com/FirstChoiceKetoGummiesKellyClarkson/
https://www.facebook.com/KellyClarksonKetoChewsGummies/
https://www.facebook.com/Renew.Calm.CBD.Gummies.Official/
https://www.facebook.com/RenewCalmCBDGummies/
|
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] |
johjonah/CUAD-Mistral-7b
|
johjonah
| 2023-12-14T14:09:00Z | 0 | 0 |
peft
|
[
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.2",
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T10:56:02Z |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: CUAD-Mistral-7b
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CUAD-Mistral-7b
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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] |
Realgon/N_bert_twitterfin_padding20model
|
Realgon
| 2023-12-14T11:02:57Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T10:58:02Z |
Entry not found
|
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] |
Norquinal/StripedHyena-Hessian-7B-claude-chat
|
Norquinal
| 2023-12-14T11:08:29Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"stripedhyena",
"text-generation",
"custom_code",
"autotrain_compatible",
"region:us"
] |
text-generation
| 2023-12-14T11:02:15Z |
Entry not found
|
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tanyamahra/tanyamahra
|
tanyamahra
| 2023-12-14T11:03:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:03:38Z |
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|
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] |
kiru1998/classification_right_false_data
|
kiru1998
| 2023-12-14T12:30:08Z | 0 | 0 | null |
[
"tensorboard",
"safetensors",
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T11:04:11Z |
---
license: apache-2.0
---
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] |
nyanxyz/fill-in-the-blank-p7-l20-e10-0
|
nyanxyz
| 2023-12-14T11:05:02Z | 0 | 0 | null |
[
"safetensors",
"autotrain",
"text-generation",
"license:other",
"region:us"
] |
text-generation
| 2023-12-14T11:04:56Z |
---
tags:
- autotrain
- text-generation
widget:
- text: "I love AutoTrain because "
license: other
---
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
```
|
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Loucha06/images
|
Loucha06
| 2023-12-14T11:05:51Z | 0 | 0 | null |
[
"region:us"
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MKS3099/Albert-finetuned-stationary-update
|
MKS3099
| 2023-12-14T11:06:14Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"albert",
"text-classification",
"generated_from_trainer",
"base_model:albert-base-v2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T11:06:11Z |
---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Albert-finetuned-stationary-update
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Albert-finetuned-stationary-update
This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7542
- Accuracy: 0.5967
- F1: 0.5862
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3976 | 1.0 | 38 | 0.8830 | 0.6033 | 0.5849 |
| 0.3105 | 2.0 | 76 | 0.9030 | 0.63 | 0.5876 |
| 0.2256 | 3.0 | 114 | 1.2156 | 0.6333 | 0.6366 |
| 0.1788 | 4.0 | 152 | 1.3055 | 0.6 | 0.5857 |
| 0.161 | 5.0 | 190 | 1.2205 | 0.59 | 0.5808 |
| 0.1304 | 6.0 | 228 | 1.5496 | 0.5933 | 0.5804 |
| 0.1046 | 7.0 | 266 | 1.6266 | 0.59 | 0.5915 |
| 0.0966 | 8.0 | 304 | 1.6807 | 0.6033 | 0.5971 |
| 0.0649 | 9.0 | 342 | 1.7279 | 0.5967 | 0.5831 |
| 0.0697 | 10.0 | 380 | 1.7542 | 0.5967 | 0.5862 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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gunkaynar/en-bert-base-multilingual-uncased-sentiment
|
gunkaynar
| 2023-12-14T11:07:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:07:53Z |
Entry not found
|
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Loucha06/LOUIS_MODEL
|
Loucha06
| 2023-12-14T11:07:59Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:07:58Z |
Entry not found
|
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iarbel/t-llama-sft_v0
|
iarbel
| 2023-12-14T11:08:33Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:08:33Z |
Entry not found
|
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gunkaynar/en-twitter-roberta-base-sentiment
|
gunkaynar
| 2023-12-14T11:09:41Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:09:41Z |
Entry not found
|
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ClumsyOnce/Viet-Laos-Translator
|
ClumsyOnce
| 2023-12-14T11:13:24Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:13:24Z |
Entry not found
|
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] |
JGlang/llama2-testconso
|
JGlang
| 2023-12-14T11:14:41Z | 0 | 0 | null |
[
"tensorboard",
"safetensors",
"autotrain",
"text-generation",
"region:us"
] |
text-generation
| 2023-12-14T11:14:34Z |
---
tags:
- autotrain
- text-generation
widget:
- text: "I love AutoTrain because "
---
# Model Trained Using AutoTrain
|
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] |
quocviethere/sentimentanalysis
|
quocviethere
| 2023-12-14T11:23:26Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:19:49Z |
Entry not found
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SebastianSchramm/phi-2-sft-full
|
SebastianSchramm
| 2023-12-14T11:20:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:20:37Z |
Entry not found
|
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AlakaDeepak/nllb-200-distilled-600M-Ma-Ta
|
AlakaDeepak
| 2023-12-14T11:21:47Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:21:47Z |
Entry not found
|
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tndklab/wav2vec-jdrt-RTSplitModel-1214-1-50epo
|
tndklab
| 2023-12-14T11:24:52Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:24:51Z |
Entry not found
|
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SAGI-1/d_data
|
SAGI-1
| 2023-12-14T11:25:20Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:25:20Z |
Entry not found
|
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hediaodiao/hediaodiao
|
hediaodiao
| 2023-12-14T11:26:28Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:26:28Z |
Entry not found
|
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bio-datasets/Mistral-7B-Instruct-v0.1-treasured-firefly-194-epoch-0
|
bio-datasets
| 2023-12-14T11:26:30Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"region:us"
] | null | 2023-12-14T11:26:28Z |
---
library_name: peft
---
## Training procedure
### Framework versions
- PEFT 0.5.0
|
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MGD-SSSS/MGD-SSSS
|
MGD-SSSS
| 2023-12-14T13:17:35Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:28:50Z |
Entry not found
|
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MKS3099/Funnel-finetuned-stationary-update
|
MKS3099
| 2023-12-14T11:29:48Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"funnel",
"text-classification",
"generated_from_trainer",
"base_model:funnel-transformer/small-base",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T11:28:51Z |
---
license: apache-2.0
base_model: funnel-transformer/small-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Funnel-finetuned-stationary-update
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Funnel-finetuned-stationary-update
This model is a fine-tuned version of [funnel-transformer/small-base](https://huggingface.co/funnel-transformer/small-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6506
- Accuracy: 0.8267
- F1: 0.8212
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.6307 | 1.0 | 38 | 0.5364 | 0.6667 | 0.5333 |
| 0.5143 | 2.0 | 76 | 0.4769 | 0.6667 | 0.5333 |
| 0.4497 | 3.0 | 114 | 0.5060 | 0.7567 | 0.7270 |
| 0.398 | 4.0 | 152 | 0.5025 | 0.8167 | 0.8082 |
| 0.3168 | 5.0 | 190 | 0.4550 | 0.8033 | 0.8072 |
| 0.2705 | 6.0 | 228 | 0.5615 | 0.8133 | 0.8034 |
| 0.2016 | 7.0 | 266 | 0.5831 | 0.83 | 0.8213 |
| 0.1492 | 8.0 | 304 | 0.6144 | 0.83 | 0.8243 |
| 0.1184 | 9.0 | 342 | 0.6269 | 0.82 | 0.8150 |
| 0.0935 | 10.0 | 380 | 0.6506 | 0.8267 | 0.8212 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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gunkaynar/en-xlnet-base-cased-SST-2
|
gunkaynar
| 2023-12-17T20:02:35Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"xlnet",
"text-classification",
"generated_from_trainer",
"base_model:xlnet-base-cased",
"license:mit",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T11:30:38Z |
---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: en-xlnet-base-cased-SST-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# en-xlnet-base-cased-SST-2
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6904
- Accuracy: 0.5373
- F1: 0.6990
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1
- Datasets 2.14.7
- Tokenizers 0.11.0
|
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] |
bio-datasets/Mistral-7B-Instruct-v0.1-blooming-thunder-195-epoch-0
|
bio-datasets
| 2023-12-14T11:35:53Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"region:us"
] | null | 2023-12-14T11:31:07Z |
---
library_name: peft
---
## Training procedure
### Framework versions
- PEFT 0.5.0
|
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] |
McCrysler/bert-trueNegative-clinical
|
McCrysler
| 2023-12-14T12:32:07Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T11:34:03Z |
Entry not found
|
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] |
hkivancoral/smids_5x_beit_base_adamax_0001_fold3
|
hkivancoral
| 2023-12-14T13:36:20Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-14T11:35:00Z |
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_beit_base_adamax_0001_fold3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.88
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_beit_base_adamax_0001_fold3
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2034
- Accuracy: 0.88
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6864 | 1.0 | 375 | 0.6860 | 0.7217 |
| 0.4252 | 2.0 | 750 | 0.6416 | 0.7633 |
| 0.3187 | 3.0 | 1125 | 0.4319 | 0.845 |
| 0.2894 | 4.0 | 1500 | 0.4449 | 0.84 |
| 0.2471 | 5.0 | 1875 | 0.4205 | 0.8483 |
| 0.1902 | 6.0 | 2250 | 0.3865 | 0.8633 |
| 0.2206 | 7.0 | 2625 | 0.4140 | 0.86 |
| 0.1469 | 8.0 | 3000 | 0.4250 | 0.875 |
| 0.0865 | 9.0 | 3375 | 0.5396 | 0.8717 |
| 0.0868 | 10.0 | 3750 | 0.6873 | 0.8583 |
| 0.0906 | 11.0 | 4125 | 0.4484 | 0.8883 |
| 0.0585 | 12.0 | 4500 | 0.6803 | 0.88 |
| 0.1093 | 13.0 | 4875 | 0.5271 | 0.8833 |
| 0.0782 | 14.0 | 5250 | 0.6855 | 0.8633 |
| 0.0163 | 15.0 | 5625 | 0.6773 | 0.865 |
| 0.0996 | 16.0 | 6000 | 0.6530 | 0.8733 |
| 0.0415 | 17.0 | 6375 | 0.8051 | 0.88 |
| 0.0673 | 18.0 | 6750 | 0.7716 | 0.88 |
| 0.1076 | 19.0 | 7125 | 0.7362 | 0.8783 |
| 0.0103 | 20.0 | 7500 | 0.7231 | 0.875 |
| 0.0579 | 21.0 | 7875 | 0.7618 | 0.88 |
| 0.0461 | 22.0 | 8250 | 0.9110 | 0.8717 |
| 0.0544 | 23.0 | 8625 | 0.7656 | 0.8767 |
| 0.0075 | 24.0 | 9000 | 0.8172 | 0.8933 |
| 0.0242 | 25.0 | 9375 | 1.0276 | 0.865 |
| 0.001 | 26.0 | 9750 | 1.1126 | 0.8717 |
| 0.0272 | 27.0 | 10125 | 0.9522 | 0.8833 |
| 0.0034 | 28.0 | 10500 | 0.9353 | 0.87 |
| 0.0223 | 29.0 | 10875 | 0.8506 | 0.8833 |
| 0.0058 | 30.0 | 11250 | 1.1236 | 0.855 |
| 0.0185 | 31.0 | 11625 | 1.0029 | 0.8733 |
| 0.0001 | 32.0 | 12000 | 0.8488 | 0.88 |
| 0.0006 | 33.0 | 12375 | 0.8729 | 0.8767 |
| 0.0005 | 34.0 | 12750 | 1.0735 | 0.875 |
| 0.0003 | 35.0 | 13125 | 1.0286 | 0.885 |
| 0.0 | 36.0 | 13500 | 0.8268 | 0.89 |
| 0.0001 | 37.0 | 13875 | 1.0063 | 0.875 |
| 0.0002 | 38.0 | 14250 | 0.9833 | 0.885 |
| 0.0009 | 39.0 | 14625 | 0.9292 | 0.8917 |
| 0.0034 | 40.0 | 15000 | 0.9953 | 0.8883 |
| 0.0 | 41.0 | 15375 | 1.0555 | 0.885 |
| 0.0 | 42.0 | 15750 | 1.0377 | 0.89 |
| 0.0 | 43.0 | 16125 | 1.1991 | 0.8717 |
| 0.0 | 44.0 | 16500 | 1.1156 | 0.8783 |
| 0.0 | 45.0 | 16875 | 1.1077 | 0.8717 |
| 0.0001 | 46.0 | 17250 | 1.0635 | 0.8817 |
| 0.0 | 47.0 | 17625 | 1.1588 | 0.8817 |
| 0.0 | 48.0 | 18000 | 1.1268 | 0.8867 |
| 0.0 | 49.0 | 18375 | 1.2011 | 0.88 |
| 0.0 | 50.0 | 18750 | 1.2034 | 0.88 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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] |
hkivancoral/smids_5x_deit_tiny_adamax_0001_fold5
|
hkivancoral
| 2023-12-17T19:19:12Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"vit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:facebook/deit-small-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-14T11:35:53Z |
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_tiny_adamax_0001_fold5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9066666666666666
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_deit_tiny_adamax_0001_fold5
This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9117
- Accuracy: 0.9067
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1964 | 1.0 | 375 | 0.3187 | 0.86 |
| 0.1451 | 2.0 | 750 | 0.2705 | 0.905 |
| 0.0998 | 3.0 | 1125 | 0.3251 | 0.905 |
| 0.0219 | 4.0 | 1500 | 0.4834 | 0.89 |
| 0.034 | 5.0 | 1875 | 0.5396 | 0.8967 |
| 0.0222 | 6.0 | 2250 | 0.4814 | 0.9133 |
| 0.0006 | 7.0 | 2625 | 0.6569 | 0.9133 |
| 0.013 | 8.0 | 3000 | 0.5398 | 0.91 |
| 0.001 | 9.0 | 3375 | 0.6798 | 0.9117 |
| 0.0003 | 10.0 | 3750 | 0.7290 | 0.9083 |
| 0.0012 | 11.0 | 4125 | 0.7598 | 0.9067 |
| 0.0 | 12.0 | 4500 | 0.6815 | 0.9167 |
| 0.0001 | 13.0 | 4875 | 0.7765 | 0.895 |
| 0.0004 | 14.0 | 5250 | 0.6391 | 0.9117 |
| 0.0001 | 15.0 | 5625 | 0.8172 | 0.9067 |
| 0.003 | 16.0 | 6000 | 0.6833 | 0.9083 |
| 0.0 | 17.0 | 6375 | 0.7002 | 0.9133 |
| 0.0103 | 18.0 | 6750 | 0.7679 | 0.91 |
| 0.0 | 19.0 | 7125 | 0.8144 | 0.905 |
| 0.0 | 20.0 | 7500 | 0.8111 | 0.905 |
| 0.0 | 21.0 | 7875 | 0.8619 | 0.9 |
| 0.0063 | 22.0 | 8250 | 0.7672 | 0.9117 |
| 0.0001 | 23.0 | 8625 | 0.8118 | 0.905 |
| 0.0 | 24.0 | 9000 | 0.7951 | 0.9133 |
| 0.0 | 25.0 | 9375 | 0.8220 | 0.9033 |
| 0.0 | 26.0 | 9750 | 0.7685 | 0.915 |
| 0.0 | 27.0 | 10125 | 0.8895 | 0.9 |
| 0.0 | 28.0 | 10500 | 0.7796 | 0.9167 |
| 0.0 | 29.0 | 10875 | 0.8774 | 0.9083 |
| 0.0031 | 30.0 | 11250 | 0.8526 | 0.905 |
| 0.0 | 31.0 | 11625 | 0.9000 | 0.9 |
| 0.0 | 32.0 | 12000 | 0.8541 | 0.9067 |
| 0.0 | 33.0 | 12375 | 0.8916 | 0.905 |
| 0.0 | 34.0 | 12750 | 0.8844 | 0.905 |
| 0.0 | 35.0 | 13125 | 0.8624 | 0.9067 |
| 0.0 | 36.0 | 13500 | 0.8971 | 0.9017 |
| 0.0 | 37.0 | 13875 | 0.8894 | 0.9083 |
| 0.003 | 38.0 | 14250 | 0.8778 | 0.905 |
| 0.0 | 39.0 | 14625 | 0.8771 | 0.9083 |
| 0.0 | 40.0 | 15000 | 0.8911 | 0.905 |
| 0.0 | 41.0 | 15375 | 0.8755 | 0.91 |
| 0.0 | 42.0 | 15750 | 0.8923 | 0.905 |
| 0.0 | 43.0 | 16125 | 0.8874 | 0.9067 |
| 0.0 | 44.0 | 16500 | 0.8938 | 0.9067 |
| 0.0 | 45.0 | 16875 | 0.8983 | 0.9067 |
| 0.0 | 46.0 | 17250 | 0.9065 | 0.9067 |
| 0.0027 | 47.0 | 17625 | 0.9068 | 0.9067 |
| 0.0 | 48.0 | 18000 | 0.9127 | 0.905 |
| 0.0 | 49.0 | 18375 | 0.9142 | 0.905 |
| 0.0023 | 50.0 | 18750 | 0.9117 | 0.9067 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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] |
abhinav-ch/pegasus-samsum
|
abhinav-ch
| 2023-12-15T06:01:05Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"pegasus",
"text2text-generation",
"generated_from_trainer",
"dataset:samsum",
"base_model:google/pegasus-cnn_dailymail",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text2text-generation
| 2023-12-14T11:37:52Z |
---
base_model: google/pegasus-cnn_dailymail
tags:
- generated_from_trainer
datasets:
- samsum
model-index:
- name: pegasus-samsum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# pegasus-samsum
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7573
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.0802 | 0.98 | 50 | 1.7573 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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] |
kwwww/bert-base-uncased-test_1_1039
|
kwwww
| 2023-12-14T16:32:48Z | 0 | 0 |
peft
|
[
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:bert-base-uncased",
"region:us"
] | null | 2023-12-14T11:39:39Z |
---
library_name: peft
base_model: bert-base-uncased
---
# Model Card for Model ID
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## Model Details
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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### Framework versions
- PEFT 0.7.1.dev0
|
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] |
SebastianSchramm/phi-2-sft-lora
|
SebastianSchramm
| 2023-12-14T11:40:13Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:40:12Z |
Entry not found
|
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] |
stvhuang/rcr-run-g6knz4zq-v2-61961-master-0_20231212T101450-ep08
|
stvhuang
| 2023-12-14T11:45:27Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"endpoints_compatible",
"region:us"
] |
feature-extraction
| 2023-12-14T11:41:47Z |
Entry not found
|
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laucoco/music
|
laucoco
| 2023-12-14T11:44:10Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:44:10Z |
Entry not found
|
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] |
gulsmyigit/RACE_t5_base
|
gulsmyigit
| 2023-12-14T11:46:04Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"t5",
"text2text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text2text-generation
| 2023-12-14T11:45:29Z |
Entry not found
|
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prajwalJumde/vlassification_13dec
|
prajwalJumde
| 2023-12-14T11:46:46Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:46:46Z |
Entry not found
|
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pariakashani/en-multinerd-ner-masked
|
pariakashani
| 2023-12-14T11:47:02Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:47:02Z |
Entry not found
|
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] |
woodyk/someone
|
woodyk
| 2023-12-14T12:16:54Z | 0 | 0 |
keras
|
[
"keras",
"anngl",
"question-answering",
"en",
"ar",
"es",
"fr",
"la",
"de",
"dataset:woodyk/my_anngl",
"dataset:codeparrot/github-code",
"dataset:wikimedia/wikipedia",
"dataset:codefuse-ai/CodeExercise-Python-27k",
"dataset:Vezora/Tested-22k-Python-Alpaca",
"arxiv:1910.09700",
"license:unknown",
"region:us"
] |
question-answering
| 2023-12-14T11:47:15Z |
---
license: unknown
datasets:
- woodyk/my_anngl
- codeparrot/github-code
- wikimedia/wikipedia
- codefuse-ai/CodeExercise-Python-27k
- Vezora/Tested-22k-Python-Alpaca
language:
- en
- ar
- es
- fr
- la
- de
metrics:
- accuracy
- code_eval
- character
library_name: keras
pipeline_tag: question-answering
tags:
- anngl
---
# Model Card for Model ID
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|
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mokkaraveendra/tesdffsdfsdfsdfsdf
|
mokkaraveendra
| 2023-12-14T11:47:21Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:47:21Z |
Entry not found
|
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Minecraft3193092-organization/minecraft-python
|
Minecraft3193092-organization
| 2023-12-14T11:53:40Z | 0 | 0 | null |
[
"license:mit",
"region:us"
] | null | 2023-12-14T11:47:47Z |
---
license: mit
---
orignal file for https://github.com/obiwac/python-minecraft-clone/
|
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] |
hkivancoral/smids_5x_beit_base_adamax_00001_fold3
|
hkivancoral
| 2023-12-14T20:30:23Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"beit",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"base_model:microsoft/beit-base-patch16-224",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-14T11:47:58Z |
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_beit_base_adamax_00001_fold3
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9133333333333333
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smids_5x_beit_base_adamax_00001_fold3
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7903
- Accuracy: 0.9133
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2779 | 1.0 | 375 | 0.3054 | 0.8733 |
| 0.2162 | 2.0 | 750 | 0.2359 | 0.92 |
| 0.1285 | 3.0 | 1125 | 0.2539 | 0.9217 |
| 0.0945 | 4.0 | 1500 | 0.2722 | 0.9233 |
| 0.101 | 5.0 | 1875 | 0.3077 | 0.92 |
| 0.0634 | 6.0 | 2250 | 0.3559 | 0.915 |
| 0.0294 | 7.0 | 2625 | 0.3959 | 0.9167 |
| 0.0374 | 8.0 | 3000 | 0.4694 | 0.9117 |
| 0.0228 | 9.0 | 3375 | 0.4761 | 0.9217 |
| 0.0104 | 10.0 | 3750 | 0.5190 | 0.925 |
| 0.0112 | 11.0 | 4125 | 0.5753 | 0.9183 |
| 0.0112 | 12.0 | 4500 | 0.5854 | 0.92 |
| 0.0095 | 13.0 | 4875 | 0.6151 | 0.9117 |
| 0.015 | 14.0 | 5250 | 0.6292 | 0.91 |
| 0.0156 | 15.0 | 5625 | 0.6403 | 0.9167 |
| 0.0162 | 16.0 | 6000 | 0.6509 | 0.9183 |
| 0.0041 | 17.0 | 6375 | 0.6568 | 0.9183 |
| 0.0184 | 18.0 | 6750 | 0.6884 | 0.915 |
| 0.0009 | 19.0 | 7125 | 0.7500 | 0.9083 |
| 0.0067 | 20.0 | 7500 | 0.7058 | 0.9183 |
| 0.0003 | 21.0 | 7875 | 0.6969 | 0.915 |
| 0.0024 | 22.0 | 8250 | 0.7459 | 0.915 |
| 0.0561 | 23.0 | 8625 | 0.6852 | 0.9183 |
| 0.0018 | 24.0 | 9000 | 0.6779 | 0.9233 |
| 0.0005 | 25.0 | 9375 | 0.7388 | 0.9183 |
| 0.0019 | 26.0 | 9750 | 0.7333 | 0.9217 |
| 0.0279 | 27.0 | 10125 | 0.7591 | 0.9133 |
| 0.0247 | 28.0 | 10500 | 0.7516 | 0.92 |
| 0.0017 | 29.0 | 10875 | 0.7698 | 0.9183 |
| 0.0267 | 30.0 | 11250 | 0.7550 | 0.9183 |
| 0.0002 | 31.0 | 11625 | 0.7870 | 0.9167 |
| 0.0313 | 32.0 | 12000 | 0.7814 | 0.9133 |
| 0.0004 | 33.0 | 12375 | 0.7692 | 0.915 |
| 0.0293 | 34.0 | 12750 | 0.7888 | 0.915 |
| 0.0001 | 35.0 | 13125 | 0.7707 | 0.915 |
| 0.0004 | 36.0 | 13500 | 0.7961 | 0.915 |
| 0.0001 | 37.0 | 13875 | 0.7594 | 0.9133 |
| 0.0 | 38.0 | 14250 | 0.7716 | 0.92 |
| 0.0004 | 39.0 | 14625 | 0.7795 | 0.92 |
| 0.0058 | 40.0 | 15000 | 0.7828 | 0.915 |
| 0.0005 | 41.0 | 15375 | 0.7680 | 0.9117 |
| 0.0001 | 42.0 | 15750 | 0.7737 | 0.915 |
| 0.0001 | 43.0 | 16125 | 0.7805 | 0.915 |
| 0.003 | 44.0 | 16500 | 0.7912 | 0.915 |
| 0.0003 | 45.0 | 16875 | 0.7859 | 0.9167 |
| 0.0104 | 46.0 | 17250 | 0.7879 | 0.9167 |
| 0.0006 | 47.0 | 17625 | 0.7848 | 0.915 |
| 0.0 | 48.0 | 18000 | 0.7845 | 0.915 |
| 0.0 | 49.0 | 18375 | 0.7887 | 0.915 |
| 0.0 | 50.0 | 18750 | 0.7903 | 0.9133 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|
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Peliin/demo
|
Peliin
| 2023-12-14T11:49:25Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:49:25Z |
Entry not found
|
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lolao/tt
|
lolao
| 2023-12-14T11:54:53Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:50:17Z |
Entry not found
|
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sahilmohsin111/bart-base-finetuned-BBC
|
sahilmohsin111
| 2023-12-14T11:51:37Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:51:37Z |
Entry not found
|
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gunkaynar/en-electra-base-sst2
|
gunkaynar
| 2023-12-14T16:59:04Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"electra",
"text-classification",
"generated_from_trainer",
"base_model:TehranNLP-org/electra-base-sst2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T11:51:38Z |
---
license: apache-2.0
base_model: TehranNLP-org/electra-base-sst2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: en-electra-base-sst2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# en-electra-base-sst2
This model is a fine-tuned version of [TehranNLP-org/electra-base-sst2](https://huggingface.co/TehranNLP-org/electra-base-sst2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5321
- Accuracy: 0.7102
- F1: 0.7417
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
### Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1
- Datasets 2.14.7
- Tokenizers 0.11.0
|
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MonsterMMORPG/rdv1
|
MonsterMMORPG
| 2023-12-14T13:00:24Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:53:19Z |
Entry not found
|
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tyseng/diffusion-tutorial-model
|
tyseng
| 2023-12-14T11:54:45Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T11:54:45Z |
Entry not found
|
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] |
SicariusSicariiStuff/Tenebra_PreAlpha_128g_3BIT
|
SicariusSicariiStuff
| 2023-12-14T12:23:04Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-14T11:55:10Z |
Entry not found
|
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] |
SicariusSicariiStuff/Tenebra_PreAlpha_128g_4BIT
|
SicariusSicariiStuff
| 2023-12-14T12:40:18Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] |
text-generation
| 2023-12-14T11:56:48Z |
Entry not found
|
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SrPrieto/q-FrozenLake-v1-4x4-noSlippery
|
SrPrieto
| 2023-12-14T12:00:45Z | 0 | 0 | null |
[
"FrozenLake-v1-4x4-no_slippery",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] |
reinforcement-learning
| 2023-12-14T11:59:06Z |
---
tags:
- FrozenLake-v1-4x4-no_slippery
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-noSlippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-4x4-no_slippery
type: FrozenLake-v1-4x4-no_slippery
metrics:
- type: mean_reward
value: 1.00 +/- 0.00
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .
## Usage
```python
model = load_from_hub(repo_id="SrPrieto/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
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] |
FutureMa/hellome
|
FutureMa
| 2023-12-14T12:12:07Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T11:59:31Z |
---
license: apache-2.0
---
|
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MDK-L/TestModel2
|
MDK-L
| 2023-12-14T12:00:03Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:00:03Z |
Entry not found
|
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ModelsForAll/Cool-1-0-0-0
|
ModelsForAll
| 2023-12-14T12:09:03Z | 0 | 0 | null |
[
"art",
"fun",
"cool",
"region:us"
] | null | 2023-12-14T12:01:40Z |
---
tags:
- art
- fun
- cool
---
“Would you like an adventure now, or would like to have your tea first?”
P. Pen
|
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] |
imyungchu/my_awesome_opus_books_model
|
imyungchu
| 2023-12-14T13:49:04Z | 0 | 0 |
transformers
|
[
"transformers",
"pytorch",
"tensorboard",
"t5",
"text2text-generation",
"generated_from_trainer",
"dataset:opus_books",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text2text-generation
| 2023-12-14T12:01:47Z |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: my_awesome_opus_books_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_books
type: opus_books
config: en-fr
split: train
args: en-fr
metrics:
- name: Bleu
type: bleu
value: 5.4017
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_opus_books_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6321
- Bleu: 5.4017
- Gen Len: 17.6165
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 1.891 | 1.0 | 3178 | 1.6559 | 5.2529 | 17.623 |
| 1.8573 | 2.0 | 6356 | 1.6321 | 5.4017 | 17.6165 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|
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SrPrieto/Taxi-v3
|
SrPrieto
| 2023-12-14T12:05:32Z | 0 | 0 | null |
[
"Taxi-v3",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] |
reinforcement-learning
| 2023-12-14T12:05:29Z |
---
tags:
- Taxi-v3
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Taxi-v3
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: Taxi-v3
type: Taxi-v3
metrics:
- type: mean_reward
value: 7.56 +/- 2.71
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **Taxi-v3**
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
## Usage
```python
model = load_from_hub(repo_id="SrPrieto/Taxi-v3", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
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] |
Ashour-Ali/Llama-2-7b-chat-finetune-crime-news-events
|
Ashour-Ali
| 2023-12-14T12:08:06Z | 0 | 0 | null |
[
"license:unknown",
"region:us"
] | null | 2023-12-14T12:08:06Z |
---
license: unknown
---
|
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bunbohue/llama2-7b_readme_summarization
|
bunbohue
| 2023-12-17T09:45:46Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-hf",
"region:us"
] | null | 2023-12-14T12:08:19Z |
---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama2-7b_readme_summarization
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama2-7b_readme_summarization
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1
|
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imdatta0/llama_2_13b_oasst_top1_2023_08_25_upNqNk_r64_lr0.0001_bg28_alpha32_run2
|
imdatta0
| 2023-12-14T12:08:39Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-13b-hf",
"region:us"
] | null | 2023-12-14T12:08:23Z |
---
base_model: meta-llama/Llama-2-13b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_2_13b_oasst_top1_2023_08_25_upNqNk_r64_lr0.0001_bg28_alpha32_run2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama_2_13b_oasst_top1_2023_08_25_upNqNk_r64_lr0.0001_bg28_alpha32_run2
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9977
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.04
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1009 | 0.04 | 32 | 1.0336 |
| 1.016 | 0.08 | 64 | 1.0133 |
| 1.0147 | 0.12 | 96 | 1.0096 |
| 0.9958 | 0.16 | 128 | 1.0064 |
| 0.9646 | 0.2 | 160 | 1.0054 |
| 1.0492 | 0.24 | 192 | 1.0046 |
| 1.0205 | 0.28 | 224 | 1.0045 |
| 1.003 | 0.32 | 256 | 1.0035 |
| 1.0151 | 0.36 | 288 | 1.0041 |
| 0.9826 | 0.4 | 320 | 1.0020 |
| 0.97 | 0.44 | 352 | 1.0023 |
| 0.9954 | 0.48 | 384 | 1.0015 |
| 1.0063 | 0.52 | 416 | 1.0008 |
| 1.0001 | 0.56 | 448 | 1.0005 |
| 1.0126 | 0.61 | 480 | 1.0003 |
| 1.005 | 0.65 | 512 | 0.9987 |
| 1.0269 | 0.69 | 544 | 0.9985 |
| 1.011 | 0.73 | 576 | 0.9983 |
| 0.9812 | 0.77 | 608 | 0.9983 |
| 1.0237 | 0.81 | 640 | 0.9982 |
| 0.9586 | 0.85 | 672 | 0.9981 |
| 1.0039 | 0.89 | 704 | 0.9976 |
| 0.9914 | 0.93 | 736 | 0.9975 |
| 0.9878 | 0.97 | 768 | 0.9977 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.5.2
- Tokenizers 0.14.1
|
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hafsanito/output_somaliv3
|
hafsanito
| 2023-12-14T12:08:46Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:08:46Z |
Entry not found
|
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] |
SAGI-1/d_adapter
|
SAGI-1
| 2023-12-14T12:10:36Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:mistralai/Mistral-7B-Instruct-v0.1",
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T12:10:27Z |
---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- generated_from_trainer
model-index:
- name: results
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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ModelsForAll/Cool-1-0-0-1
|
ModelsForAll
| 2023-12-14T12:11:57Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:10:32Z |
“Would you like an adventure now, or would like to have your tea first?” P. Pen
|
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owanr/ghc-roberta-base-inter-data-frequency-model_annots
|
owanr
| 2023-12-14T13:44:26Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"region:us"
] | null | 2023-12-14T12:12:14Z |
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: ghc-roberta-base-inter-data-frequency-model_annots
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ghc-roberta-base-inter-data-frequency-model_annots
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 51.7977
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 21.5116 | 1.0 | 345 | 50.5830 |
| 18.4644 | 2.0 | 690 | 50.9533 |
| 16.5572 | 3.0 | 1035 | 51.4882 |
| 19.8724 | 4.0 | 1380 | 51.7977 |
| 17.4379 | 5.0 | 1725 | 51.7977 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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] |
aaa12963337/msi-nat-mini
|
aaa12963337
| 2023-12-16T11:02:23Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"nat",
"image-classification",
"generated_from_trainer",
"dataset:imagefolder",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
image-classification
| 2023-12-14T12:13:53Z |
---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: msi-nat-mini
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6308708414872799
- name: F1
type: f1
value: 0.47632740072381147
- name: Precision
type: precision
value: 0.6193914388860238
- name: Recall
type: recall
value: 0.3869512686266613
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# msi-nat-mini
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8600
- Accuracy: 0.6309
- F1: 0.4763
- Precision: 0.6194
- Recall: 0.3870
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5496 | 1.0 | 2015 | 0.7573 | 0.5955 | 0.4196 | 0.5559 | 0.3369 |
| 0.4807 | 2.0 | 4031 | 0.7416 | 0.6309 | 0.4981 | 0.6074 | 0.4222 |
| 0.4235 | 3.0 | 6047 | 0.7680 | 0.6325 | 0.5047 | 0.6076 | 0.4317 |
| 0.3879 | 4.0 | 8063 | 0.7875 | 0.6339 | 0.4923 | 0.6179 | 0.4092 |
| 0.3702 | 5.0 | 10078 | 0.7923 | 0.6383 | 0.5128 | 0.6168 | 0.4388 |
| 0.3568 | 6.0 | 12094 | 0.8311 | 0.6313 | 0.4969 | 0.6090 | 0.4197 |
| 0.3661 | 7.0 | 14110 | 0.8345 | 0.6316 | 0.4843 | 0.6166 | 0.3987 |
| 0.354 | 8.0 | 16126 | 0.8501 | 0.6305 | 0.4800 | 0.6162 | 0.3931 |
| 0.3569 | 9.0 | 18141 | 0.8552 | 0.6318 | 0.4809 | 0.6193 | 0.3931 |
| 0.3536 | 10.0 | 20150 | 0.8600 | 0.6309 | 0.4763 | 0.6194 | 0.3870 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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Xing01/yi-chat-6B-GGUF
|
Xing01
| 2023-12-14T12:14:39Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:14:39Z |
Entry not found
|
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] |
jan-hq/Solar-10.7B-SLERP-GGUF
|
jan-hq
| 2023-12-14T12:38:00Z | 0 | 4 | null |
[
"gguf",
"en",
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T12:16:35Z |
---
license: apache-2.0
language:
- en
---
<!-- header start -->
<!-- 200823 -->
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://github.com/janhq/jan/assets/89722390/35daac7d-b895-487c-a6ac-6663daaad78e" alt="Jan banner" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
<p align="center">
<a href="https://jan.ai/">Jan</a
>
- <a href="https://discord.gg/AsJ8krTT3N">Discord</a>
</p>
<!-- header end -->
# Model Description
This model uses the `Slerp` merge method from the best models on 14th Dec on the [OpenLLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard):
1. [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)
2. [janhq/Pandora-v1-10.7B](https://huggingface.co/janhq/Pandora-v1-10.7B)
- base model: [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0)
The yaml config file for this model is here:
```yaml
slices:
- sources:
- model: upstage/SOLAR-10.7B-Instruct-v1.0
layer_range: [0, 48]
- model: janhq/Pandora-v1-10.7B
layer_range: [0, 48]
merge_method: slerp
base_model: upstage/SOLAR-10.7B-Instruct-v1.0
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
```
# Prompt template
- **ChatML**
```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
# Run this model
You can run this model using [Jan](https://jan.ai/) on Mac, Windows, or Linux.
**Jan is an open source, ChatGPT alternative that is:**
💻 **100% offline on your machine**: Your conversations remain confidential, and visible only to you.
🗂️ **An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time.
🌐 **OpenAI Compatible**: Local server on port `
1337` with OpenAI compatible endpoints
🌍 **Open Source & Free**: We build in public; check out our [Github](https://github.com/janhq)
- Please use the [Solar-10.7B-SLERP-GGUF](https://huggingface.co/janhq/Solar-10.7B-SLERP-GGUF) when using on Jan.
# About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.
Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.
# Jan Model Merger
This is a test project for merging models.
# Open LLM Leaderboard Evaluation Results
Detailed results can be found here.
| Metric | Value |
|-----------------------|---------------------------|
| Avg. | ?|
| ARC (25-shot) | ? |
| HellaSwag (10-shot) | ? |
| MMLU (5-shot) | ?|
| TruthfulQA (0-shot) | ? |
| Winogrande (5-shot) | ? |
| GSM8K (5-shot) | ? |
# Acknowlegement
- [mergekit](https://github.com/cg123/mergekit)
- [DARE](https://github.com/yule-BUAA/MergeLM/blob/main/README.md)
- [SLERP](https://github.com/Digitous/LLM-SLERP-Merge)
- [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
|
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st-karlos-efood/setfit-ethos-multilabel-example
|
st-karlos-efood
| 2023-12-14T12:17:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:16:39Z |
---
{}
---
Test
|
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] |
axljeremy7/bert-base-uncased-finetuned-stsb-finetuned-stsb
|
axljeremy7
| 2023-12-14T12:25:20Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"bert",
"text-classification",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T12:17:24Z |
Entry not found
|
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] |
alitolga/deberta-base-peft
|
alitolga
| 2023-12-17T21:13:26Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:microsoft/deberta-base",
"license:mit",
"region:us"
] | null | 2023-12-14T12:17:28Z |
---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
model-index:
- name: deberta-base-peft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-base-peft
This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5691
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4191 | 1.0 | 389 | 1.2536 |
| 1.2007 | 2.0 | 778 | 0.6712 |
| 0.9788 | 3.0 | 1167 | 0.5691 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
|
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] |
jcolab5/llama-2-7b-chat-hf-instruct-medical-assistance
|
jcolab5
| 2023-12-14T12:34:49Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"llama",
"text-generation",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-14T12:22:40Z |
Entry not found
|
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Alirani/distilgpt2-tweet-generator
|
Alirani
| 2023-12-14T13:56:20Z | 0 | 0 |
transformers
|
[
"transformers",
"tf",
"tensorboard",
"gpt2",
"text-generation",
"generated_from_keras_callback",
"base_model:distilgpt2",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-14T12:22:57Z |
---
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_keras_callback
model-index:
- name: Alirani/distilgpt2-tweet-generator
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Alirani/distilgpt2-tweet-generator
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 3.6901
- Validation Loss: 3.6474
- Epoch: 3
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 4.2051 | 3.9133 | 0 |
| 3.9132 | 3.7845 | 1 |
| 3.7841 | 3.7018 | 2 |
| 3.6901 | 3.6474 | 3 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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bunbohue/llama2-7b-chat_readme_summarization
|
bunbohue
| 2023-12-15T07:44:17Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:meta-llama/Llama-2-7b-chat-hf",
"region:us"
] | null | 2023-12-14T12:23:05Z |
---
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
- generated_from_trainer
model-index:
- name: llama2-7b-chat_readme_summarization
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# llama2-7b-chat_readme_summarization
This model is a fine-tuned version of [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1
|
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soniarocca31/modello_finetuning1
|
soniarocca31
| 2023-12-14T12:24:41Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"distilbert",
"text-classification",
"generated_from_trainer",
"dataset:swiss_law_area_prediction",
"base_model:distilbert-base-multilingual-cased",
"license:apache-2.0",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-classification
| 2023-12-14T12:24:12Z |
---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
datasets:
- swiss_law_area_prediction
metrics:
- precision
- recall
- f1
model-index:
- name: modello_finetuning1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: swiss_law_area_prediction
type: swiss_law_area_prediction
config: main
split: validation
args: main
metrics:
- name: Precision
type: precision
value: 0.9922018189992046
- name: Recall
type: recall
value: 0.9901734200771951
- name: F1
type: f1
value: 0.9911413155243709
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# modello_finetuning1
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the swiss_law_area_prediction dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0506
- Precision: 0.9922
- Recall: 0.9902
- F1: 0.9911
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.0834 | 0.38 | 500 | 0.1812 | 0.9793 | 0.9677 | 0.9730 |
| 0.1029 | 0.76 | 1000 | 0.0973 | 0.9875 | 0.9834 | 0.9854 |
| 0.0066 | 1.15 | 1500 | 0.0647 | 0.9864 | 0.9886 | 0.9875 |
| 0.0008 | 1.53 | 2000 | 0.0619 | 0.9913 | 0.9893 | 0.9902 |
| 0.0003 | 1.91 | 2500 | 0.0506 | 0.9922 | 0.9902 | 0.9911 |
### Framework versions
- Transformers 4.36.1
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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hf-100/mssb
|
hf-100
| 2023-12-14T12:25:33Z | 0 | 0 | null |
[
"safetensors",
"license:openrail",
"region:us"
] | null | 2023-12-14T12:24:47Z |
---
license: openrail
---
|
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AdnanRiaz107/codebertmlmPEFT-finetuned-the-stack-bash
|
AdnanRiaz107
| 2023-12-14T12:25:00Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:25:00Z |
Entry not found
|
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DariaMayak/irina
|
DariaMayak
| 2023-12-14T12:25:17Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:25:17Z |
Entry not found
|
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kwwww/bert-base-uncased_1_1039_token_headwise
|
kwwww
| 2023-12-15T05:03:32Z | 0 | 0 | null |
[
"pytorch",
"generated_from_trainer",
"dataset:bionlp2004",
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T12:29:40Z |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- bionlp2004
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased_1_1039_token_headwise
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-uncased_1_1039_token_headwise
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the bionlp2004 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7082
- Precision: 0.7269
- Recall: 0.7596
- F1: 0.7429
- Accuracy: 0.9313
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 65 | 0.3696 | 0.3899 | 0.4363 | 0.4118 | 0.8645 |
| No log | 2.0 | 130 | 0.2642 | 0.5334 | 0.6793 | 0.5975 | 0.9087 |
| No log | 3.0 | 195 | 0.2561 | 0.6154 | 0.6447 | 0.6297 | 0.9128 |
| No log | 4.0 | 260 | 0.2290 | 0.6377 | 0.7034 | 0.6690 | 0.9261 |
| No log | 5.0 | 325 | 0.2333 | 0.6567 | 0.7191 | 0.6865 | 0.9252 |
| No log | 6.0 | 390 | 0.2503 | 0.6601 | 0.7355 | 0.6957 | 0.9241 |
| No log | 7.0 | 455 | 0.2347 | 0.6643 | 0.7317 | 0.6964 | 0.9290 |
| 0.2402 | 8.0 | 520 | 0.2530 | 0.6651 | 0.7241 | 0.6933 | 0.9284 |
| 0.2402 | 9.0 | 585 | 0.2828 | 0.6476 | 0.7547 | 0.6970 | 0.9231 |
| 0.2402 | 10.0 | 650 | 0.2752 | 0.6853 | 0.6985 | 0.6919 | 0.9236 |
| 0.2402 | 11.0 | 715 | 0.2902 | 0.6817 | 0.7003 | 0.6909 | 0.9249 |
| 0.2402 | 12.0 | 780 | 0.3254 | 0.6492 | 0.7113 | 0.6789 | 0.9192 |
| 0.2402 | 13.0 | 845 | 0.3136 | 0.6856 | 0.6638 | 0.6745 | 0.9242 |
| 0.2402 | 14.0 | 910 | 0.3013 | 0.6657 | 0.7229 | 0.6931 | 0.9262 |
| 0.2402 | 15.0 | 975 | 0.3038 | 0.6879 | 0.7290 | 0.7078 | 0.9280 |
| 0.0852 | 16.0 | 1040 | 0.3190 | 0.6791 | 0.7063 | 0.6924 | 0.9271 |
| 0.0852 | 17.0 | 1105 | 0.3263 | 0.6541 | 0.7394 | 0.6942 | 0.9260 |
| 0.0852 | 18.0 | 1170 | 0.3186 | 0.6854 | 0.7263 | 0.7053 | 0.9281 |
| 0.0852 | 19.0 | 1235 | 0.3428 | 0.6758 | 0.7272 | 0.7006 | 0.9271 |
| 0.0852 | 20.0 | 1300 | 0.3660 | 0.6801 | 0.7043 | 0.6920 | 0.9220 |
| 0.0852 | 21.0 | 1365 | 0.3289 | 0.6802 | 0.7196 | 0.6993 | 0.9282 |
| 0.0852 | 22.0 | 1430 | 0.3304 | 0.6701 | 0.7317 | 0.6996 | 0.9262 |
| 0.0852 | 23.0 | 1495 | 0.3442 | 0.6732 | 0.7437 | 0.7067 | 0.9281 |
| 0.0541 | 24.0 | 1560 | 0.3710 | 0.6784 | 0.7367 | 0.7064 | 0.9272 |
| 0.0541 | 25.0 | 1625 | 0.3351 | 0.6773 | 0.7247 | 0.7002 | 0.9276 |
| 0.0541 | 26.0 | 1690 | 0.3637 | 0.6761 | 0.7398 | 0.7065 | 0.9275 |
| 0.0541 | 27.0 | 1755 | 0.3623 | 0.6610 | 0.7340 | 0.6956 | 0.9253 |
| 0.0541 | 28.0 | 1820 | 0.4048 | 0.6703 | 0.7364 | 0.7018 | 0.9245 |
| 0.0541 | 29.0 | 1885 | 0.3750 | 0.6756 | 0.7254 | 0.6996 | 0.9260 |
| 0.0541 | 30.0 | 1950 | 0.3637 | 0.6782 | 0.7547 | 0.7144 | 0.9287 |
| 0.0414 | 31.0 | 2015 | 0.3530 | 0.6604 | 0.7643 | 0.7086 | 0.9271 |
| 0.0414 | 32.0 | 2080 | 0.3778 | 0.6853 | 0.7419 | 0.7125 | 0.9286 |
| 0.0414 | 33.0 | 2145 | 0.3664 | 0.6740 | 0.7095 | 0.6913 | 0.9251 |
| 0.0414 | 34.0 | 2210 | 0.3695 | 0.6737 | 0.7470 | 0.7085 | 0.9271 |
| 0.0414 | 35.0 | 2275 | 0.3910 | 0.6824 | 0.7432 | 0.7115 | 0.9295 |
| 0.0414 | 36.0 | 2340 | 0.3814 | 0.6707 | 0.7412 | 0.7042 | 0.9263 |
| 0.0414 | 37.0 | 2405 | 0.3774 | 0.6760 | 0.7493 | 0.7108 | 0.9281 |
| 0.0414 | 38.0 | 2470 | 0.4391 | 0.6640 | 0.7504 | 0.7045 | 0.9249 |
| 0.0359 | 39.0 | 2535 | 0.3875 | 0.6797 | 0.7169 | 0.6978 | 0.9269 |
| 0.0359 | 40.0 | 2600 | 0.4387 | 0.6769 | 0.7021 | 0.6893 | 0.9228 |
| 0.0359 | 41.0 | 2665 | 0.4005 | 0.6776 | 0.7131 | 0.6949 | 0.9251 |
| 0.0359 | 42.0 | 2730 | 0.4221 | 0.6899 | 0.7301 | 0.7094 | 0.9271 |
| 0.0359 | 43.0 | 2795 | 0.4041 | 0.7058 | 0.7111 | 0.7085 | 0.9280 |
| 0.0359 | 44.0 | 2860 | 0.4384 | 0.6735 | 0.7198 | 0.6959 | 0.9238 |
| 0.0359 | 45.0 | 2925 | 0.3973 | 0.6865 | 0.7513 | 0.7175 | 0.9292 |
| 0.0359 | 46.0 | 2990 | 0.4180 | 0.6847 | 0.7337 | 0.7083 | 0.9263 |
| 0.0315 | 47.0 | 3055 | 0.3918 | 0.6697 | 0.7650 | 0.7142 | 0.9278 |
| 0.0315 | 48.0 | 3120 | 0.4501 | 0.6971 | 0.7387 | 0.7173 | 0.9282 |
| 0.0315 | 49.0 | 3185 | 0.4052 | 0.6633 | 0.7603 | 0.7085 | 0.9255 |
| 0.0315 | 50.0 | 3250 | 0.4000 | 0.7034 | 0.7407 | 0.7216 | 0.9306 |
| 0.0315 | 51.0 | 3315 | 0.4208 | 0.6809 | 0.7274 | 0.7034 | 0.9269 |
| 0.0315 | 52.0 | 3380 | 0.4207 | 0.6973 | 0.7362 | 0.7162 | 0.9295 |
| 0.0315 | 53.0 | 3445 | 0.4629 | 0.6726 | 0.7410 | 0.7052 | 0.9244 |
| 0.028 | 54.0 | 3510 | 0.4835 | 0.6730 | 0.7128 | 0.6923 | 0.9227 |
| 0.028 | 55.0 | 3575 | 0.4565 | 0.6821 | 0.7209 | 0.7009 | 0.9262 |
| 0.028 | 56.0 | 3640 | 0.4365 | 0.6909 | 0.7351 | 0.7123 | 0.9284 |
| 0.028 | 57.0 | 3705 | 0.4457 | 0.6844 | 0.7221 | 0.7028 | 0.9266 |
| 0.028 | 58.0 | 3770 | 0.4455 | 0.6926 | 0.7266 | 0.7092 | 0.9271 |
| 0.028 | 59.0 | 3835 | 0.4607 | 0.6756 | 0.7441 | 0.7082 | 0.9265 |
| 0.028 | 60.0 | 3900 | 0.4574 | 0.6908 | 0.7221 | 0.7061 | 0.9271 |
| 0.028 | 61.0 | 3965 | 0.4359 | 0.6732 | 0.7473 | 0.7083 | 0.9273 |
| 0.0263 | 62.0 | 4030 | 0.4431 | 0.6921 | 0.7362 | 0.7134 | 0.9279 |
| 0.0263 | 63.0 | 4095 | 0.4631 | 0.6820 | 0.7207 | 0.7008 | 0.9253 |
| 0.0263 | 64.0 | 4160 | 0.4473 | 0.6867 | 0.7398 | 0.7123 | 0.9269 |
| 0.0263 | 65.0 | 4225 | 0.4193 | 0.6793 | 0.7380 | 0.7074 | 0.9281 |
| 0.0263 | 66.0 | 4290 | 0.4733 | 0.6808 | 0.7326 | 0.7058 | 0.9247 |
| 0.0263 | 67.0 | 4355 | 0.5110 | 0.6847 | 0.6868 | 0.6858 | 0.9202 |
| 0.0263 | 68.0 | 4420 | 0.4554 | 0.6948 | 0.7165 | 0.7055 | 0.9261 |
| 0.0263 | 69.0 | 4485 | 0.4947 | 0.6892 | 0.7252 | 0.7067 | 0.9260 |
| 0.0237 | 70.0 | 4550 | 0.4514 | 0.6995 | 0.7265 | 0.7127 | 0.9283 |
| 0.0237 | 71.0 | 4615 | 0.4633 | 0.6811 | 0.7299 | 0.7046 | 0.9249 |
| 0.0237 | 72.0 | 4680 | 0.4369 | 0.6855 | 0.7284 | 0.7063 | 0.9258 |
| 0.0237 | 73.0 | 4745 | 0.4336 | 0.6898 | 0.7491 | 0.7182 | 0.9293 |
| 0.0237 | 74.0 | 4810 | 0.4685 | 0.6838 | 0.7097 | 0.6965 | 0.9259 |
| 0.0237 | 75.0 | 4875 | 0.4324 | 0.7028 | 0.7434 | 0.7225 | 0.9304 |
| 0.0237 | 76.0 | 4940 | 0.4981 | 0.6559 | 0.7120 | 0.6828 | 0.9216 |
| 0.0243 | 77.0 | 5005 | 0.4377 | 0.6961 | 0.7502 | 0.7221 | 0.9299 |
| 0.0243 | 78.0 | 5070 | 0.4363 | 0.6692 | 0.7428 | 0.7041 | 0.9263 |
| 0.0243 | 79.0 | 5135 | 0.4877 | 0.6955 | 0.7315 | 0.7131 | 0.9278 |
| 0.0243 | 80.0 | 5200 | 0.4440 | 0.6932 | 0.7450 | 0.7182 | 0.9284 |
| 0.0243 | 81.0 | 5265 | 0.4880 | 0.6928 | 0.7324 | 0.7121 | 0.9260 |
| 0.0243 | 82.0 | 5330 | 0.4389 | 0.6716 | 0.7351 | 0.7019 | 0.9246 |
| 0.0243 | 83.0 | 5395 | 0.4681 | 0.6731 | 0.7463 | 0.7078 | 0.9257 |
| 0.0243 | 84.0 | 5460 | 0.5041 | 0.6981 | 0.7238 | 0.7107 | 0.9263 |
| 0.0196 | 85.0 | 5525 | 0.4899 | 0.6760 | 0.7454 | 0.7090 | 0.9248 |
| 0.0196 | 86.0 | 5590 | 0.4508 | 0.6796 | 0.7396 | 0.7083 | 0.9272 |
| 0.0196 | 87.0 | 5655 | 0.4639 | 0.6957 | 0.7612 | 0.7270 | 0.9293 |
| 0.0196 | 88.0 | 5720 | 0.5052 | 0.7167 | 0.7052 | 0.7109 | 0.9267 |
| 0.0196 | 89.0 | 5785 | 0.4500 | 0.7028 | 0.7338 | 0.7180 | 0.9286 |
| 0.0196 | 90.0 | 5850 | 0.4773 | 0.6738 | 0.7650 | 0.7165 | 0.9274 |
| 0.0196 | 91.0 | 5915 | 0.4894 | 0.6778 | 0.6957 | 0.6866 | 0.9231 |
| 0.0196 | 92.0 | 5980 | 0.5065 | 0.6633 | 0.7625 | 0.7095 | 0.9250 |
| 0.0204 | 93.0 | 6045 | 0.4610 | 0.6983 | 0.7405 | 0.7188 | 0.9284 |
| 0.0204 | 94.0 | 6110 | 0.4562 | 0.6939 | 0.7421 | 0.7172 | 0.9286 |
| 0.0204 | 95.0 | 6175 | 0.5018 | 0.6847 | 0.7436 | 0.7129 | 0.9261 |
| 0.0204 | 96.0 | 6240 | 0.4578 | 0.6967 | 0.7238 | 0.7099 | 0.9263 |
| 0.0204 | 97.0 | 6305 | 0.4758 | 0.6921 | 0.7578 | 0.7235 | 0.9295 |
| 0.0204 | 98.0 | 6370 | 0.4724 | 0.6786 | 0.7434 | 0.7095 | 0.9272 |
| 0.0204 | 99.0 | 6435 | 0.4887 | 0.6815 | 0.7376 | 0.7085 | 0.9253 |
| 0.019 | 100.0 | 6500 | 0.4965 | 0.6866 | 0.7598 | 0.7213 | 0.9277 |
| 0.019 | 101.0 | 6565 | 0.4829 | 0.6981 | 0.7382 | 0.7175 | 0.9279 |
| 0.019 | 102.0 | 6630 | 0.4491 | 0.6997 | 0.7549 | 0.7263 | 0.9302 |
| 0.019 | 103.0 | 6695 | 0.4637 | 0.6858 | 0.7484 | 0.7157 | 0.9263 |
| 0.019 | 104.0 | 6760 | 0.5521 | 0.7089 | 0.6825 | 0.6955 | 0.9219 |
| 0.019 | 105.0 | 6825 | 0.5193 | 0.6947 | 0.7011 | 0.6979 | 0.9229 |
| 0.019 | 106.0 | 6890 | 0.4682 | 0.6947 | 0.7385 | 0.7160 | 0.9275 |
| 0.019 | 107.0 | 6955 | 0.4664 | 0.7038 | 0.7202 | 0.7119 | 0.9270 |
| 0.0193 | 108.0 | 7020 | 0.5158 | 0.6891 | 0.7122 | 0.7005 | 0.9253 |
| 0.0193 | 109.0 | 7085 | 0.5069 | 0.6761 | 0.7337 | 0.7037 | 0.9251 |
| 0.0193 | 110.0 | 7150 | 0.5207 | 0.7023 | 0.7045 | 0.7034 | 0.9229 |
| 0.0193 | 111.0 | 7215 | 0.5142 | 0.6748 | 0.7443 | 0.7078 | 0.9242 |
| 0.0193 | 112.0 | 7280 | 0.4928 | 0.7003 | 0.7117 | 0.7060 | 0.9262 |
| 0.0193 | 113.0 | 7345 | 0.5048 | 0.6859 | 0.7299 | 0.7072 | 0.9270 |
| 0.0193 | 114.0 | 7410 | 0.4970 | 0.7062 | 0.7319 | 0.7188 | 0.9281 |
| 0.0193 | 115.0 | 7475 | 0.4890 | 0.6929 | 0.7493 | 0.7200 | 0.9276 |
| 0.0159 | 116.0 | 7540 | 0.4921 | 0.6845 | 0.7499 | 0.7157 | 0.9256 |
| 0.0159 | 117.0 | 7605 | 0.5174 | 0.6938 | 0.6944 | 0.6941 | 0.9228 |
| 0.0159 | 118.0 | 7670 | 0.4855 | 0.6961 | 0.7491 | 0.7217 | 0.9276 |
| 0.0159 | 119.0 | 7735 | 0.4858 | 0.6990 | 0.7239 | 0.7113 | 0.9274 |
| 0.0159 | 120.0 | 7800 | 0.4926 | 0.7076 | 0.7529 | 0.7295 | 0.9298 |
| 0.0159 | 121.0 | 7865 | 0.4701 | 0.7045 | 0.7337 | 0.7188 | 0.9294 |
| 0.0159 | 122.0 | 7930 | 0.4705 | 0.7139 | 0.7315 | 0.7226 | 0.9297 |
| 0.0159 | 123.0 | 7995 | 0.4811 | 0.6975 | 0.7565 | 0.7258 | 0.9285 |
| 0.0178 | 124.0 | 8060 | 0.4861 | 0.7013 | 0.7455 | 0.7228 | 0.9290 |
| 0.0178 | 125.0 | 8125 | 0.4886 | 0.6899 | 0.7571 | 0.7219 | 0.9280 |
| 0.0178 | 126.0 | 8190 | 0.5003 | 0.6926 | 0.7551 | 0.7225 | 0.9280 |
| 0.0178 | 127.0 | 8255 | 0.5223 | 0.7013 | 0.7436 | 0.7218 | 0.9277 |
| 0.0178 | 128.0 | 8320 | 0.5101 | 0.7108 | 0.7308 | 0.7207 | 0.9284 |
| 0.0178 | 129.0 | 8385 | 0.5346 | 0.7061 | 0.7220 | 0.7139 | 0.9257 |
| 0.0178 | 130.0 | 8450 | 0.5603 | 0.6904 | 0.7529 | 0.7203 | 0.9259 |
| 0.0132 | 131.0 | 8515 | 0.5077 | 0.7088 | 0.7347 | 0.7215 | 0.9276 |
| 0.0132 | 132.0 | 8580 | 0.4954 | 0.7030 | 0.7302 | 0.7164 | 0.9296 |
| 0.0132 | 133.0 | 8645 | 0.5421 | 0.6945 | 0.7119 | 0.7031 | 0.9264 |
| 0.0132 | 134.0 | 8710 | 0.5303 | 0.6992 | 0.7493 | 0.7234 | 0.9278 |
| 0.0132 | 135.0 | 8775 | 0.5150 | 0.7030 | 0.7405 | 0.7213 | 0.9282 |
| 0.0132 | 136.0 | 8840 | 0.5388 | 0.6603 | 0.7401 | 0.6980 | 0.9228 |
| 0.0132 | 137.0 | 8905 | 0.5005 | 0.6944 | 0.7463 | 0.7194 | 0.9279 |
| 0.0132 | 138.0 | 8970 | 0.5137 | 0.6942 | 0.7482 | 0.7202 | 0.9265 |
| 0.0148 | 139.0 | 9035 | 0.5623 | 0.6976 | 0.7265 | 0.7117 | 0.9250 |
| 0.0148 | 140.0 | 9100 | 0.5130 | 0.6852 | 0.7436 | 0.7132 | 0.9264 |
| 0.0148 | 141.0 | 9165 | 0.5298 | 0.6817 | 0.7448 | 0.7119 | 0.9263 |
| 0.0148 | 142.0 | 9230 | 0.5653 | 0.6702 | 0.7326 | 0.7000 | 0.9232 |
| 0.0148 | 143.0 | 9295 | 0.5240 | 0.6951 | 0.7360 | 0.7149 | 0.9262 |
| 0.0148 | 144.0 | 9360 | 0.5129 | 0.7194 | 0.7450 | 0.7320 | 0.9304 |
| 0.0148 | 145.0 | 9425 | 0.5343 | 0.6809 | 0.7491 | 0.7134 | 0.9261 |
| 0.0148 | 146.0 | 9490 | 0.5193 | 0.6888 | 0.7198 | 0.7039 | 0.9257 |
| 0.0137 | 147.0 | 9555 | 0.5247 | 0.7087 | 0.7011 | 0.7049 | 0.9246 |
| 0.0137 | 148.0 | 9620 | 0.5176 | 0.6948 | 0.7621 | 0.7269 | 0.9273 |
| 0.0137 | 149.0 | 9685 | 0.5340 | 0.7055 | 0.7270 | 0.7161 | 0.9274 |
| 0.0137 | 150.0 | 9750 | 0.5710 | 0.6964 | 0.7358 | 0.7156 | 0.9252 |
| 0.0137 | 151.0 | 9815 | 0.5284 | 0.7119 | 0.7234 | 0.7176 | 0.9279 |
| 0.0137 | 152.0 | 9880 | 0.5471 | 0.6905 | 0.7335 | 0.7113 | 0.9267 |
| 0.0137 | 153.0 | 9945 | 0.5209 | 0.6932 | 0.7427 | 0.7171 | 0.9272 |
| 0.0134 | 154.0 | 10010 | 0.5243 | 0.6907 | 0.7356 | 0.7125 | 0.9262 |
| 0.0134 | 155.0 | 10075 | 0.5613 | 0.7104 | 0.7409 | 0.7253 | 0.9296 |
| 0.0134 | 156.0 | 10140 | 0.5605 | 0.7080 | 0.7202 | 0.7140 | 0.9258 |
| 0.0134 | 157.0 | 10205 | 0.5246 | 0.6943 | 0.7574 | 0.7245 | 0.9291 |
| 0.0134 | 158.0 | 10270 | 0.5370 | 0.6696 | 0.7459 | 0.7057 | 0.9245 |
| 0.0134 | 159.0 | 10335 | 0.5182 | 0.6915 | 0.7347 | 0.7125 | 0.9275 |
| 0.0134 | 160.0 | 10400 | 0.5131 | 0.6984 | 0.7147 | 0.7065 | 0.9264 |
| 0.0134 | 161.0 | 10465 | 0.5083 | 0.7124 | 0.7259 | 0.7191 | 0.9283 |
| 0.0122 | 162.0 | 10530 | 0.5521 | 0.6975 | 0.7392 | 0.7178 | 0.9261 |
| 0.0122 | 163.0 | 10595 | 0.5295 | 0.6910 | 0.7373 | 0.7134 | 0.9261 |
| 0.0122 | 164.0 | 10660 | 0.5166 | 0.7044 | 0.7515 | 0.7272 | 0.9283 |
| 0.0122 | 165.0 | 10725 | 0.5229 | 0.7238 | 0.7126 | 0.7181 | 0.9270 |
| 0.0122 | 166.0 | 10790 | 0.5631 | 0.6881 | 0.7590 | 0.7218 | 0.9258 |
| 0.0122 | 167.0 | 10855 | 0.5600 | 0.7097 | 0.7142 | 0.7120 | 0.9269 |
| 0.0122 | 168.0 | 10920 | 0.5865 | 0.6786 | 0.7301 | 0.7034 | 0.9242 |
| 0.0122 | 169.0 | 10985 | 0.5617 | 0.7166 | 0.6993 | 0.7078 | 0.9249 |
| 0.0112 | 170.0 | 11050 | 0.5454 | 0.7186 | 0.7225 | 0.7205 | 0.9294 |
| 0.0112 | 171.0 | 11115 | 0.5320 | 0.7006 | 0.7401 | 0.7199 | 0.9271 |
| 0.0112 | 172.0 | 11180 | 0.5171 | 0.6898 | 0.7441 | 0.7159 | 0.9283 |
| 0.0112 | 173.0 | 11245 | 0.5290 | 0.7031 | 0.7515 | 0.7265 | 0.9301 |
| 0.0112 | 174.0 | 11310 | 0.4976 | 0.6955 | 0.7659 | 0.7290 | 0.9287 |
| 0.0112 | 175.0 | 11375 | 0.5538 | 0.7037 | 0.7344 | 0.7187 | 0.9275 |
| 0.0112 | 176.0 | 11440 | 0.5517 | 0.6980 | 0.7385 | 0.7177 | 0.9291 |
| 0.0105 | 177.0 | 11505 | 0.5294 | 0.6874 | 0.7571 | 0.7205 | 0.9275 |
| 0.0105 | 178.0 | 11570 | 0.5458 | 0.7025 | 0.7373 | 0.7194 | 0.9274 |
| 0.0105 | 179.0 | 11635 | 0.5323 | 0.6903 | 0.7477 | 0.7178 | 0.9286 |
| 0.0105 | 180.0 | 11700 | 0.5463 | 0.7042 | 0.7529 | 0.7278 | 0.9296 |
| 0.0105 | 181.0 | 11765 | 0.5385 | 0.6939 | 0.7619 | 0.7264 | 0.9279 |
| 0.0105 | 182.0 | 11830 | 0.5186 | 0.6954 | 0.7472 | 0.7204 | 0.9274 |
| 0.0105 | 183.0 | 11895 | 0.5429 | 0.6931 | 0.7661 | 0.7277 | 0.9283 |
| 0.0105 | 184.0 | 11960 | 0.5033 | 0.7035 | 0.7427 | 0.7226 | 0.9304 |
| 0.0096 | 185.0 | 12025 | 0.5510 | 0.7063 | 0.7290 | 0.7175 | 0.9270 |
| 0.0096 | 186.0 | 12090 | 0.5444 | 0.7058 | 0.7461 | 0.7254 | 0.9303 |
| 0.0096 | 187.0 | 12155 | 0.5375 | 0.6940 | 0.7542 | 0.7228 | 0.9289 |
| 0.0096 | 188.0 | 12220 | 0.5489 | 0.7102 | 0.7382 | 0.7239 | 0.9278 |
| 0.0096 | 189.0 | 12285 | 0.5960 | 0.6923 | 0.7223 | 0.7070 | 0.9250 |
| 0.0096 | 190.0 | 12350 | 0.5823 | 0.7116 | 0.7675 | 0.7385 | 0.9287 |
| 0.0096 | 191.0 | 12415 | 0.5430 | 0.7159 | 0.7551 | 0.7350 | 0.9307 |
| 0.0096 | 192.0 | 12480 | 0.5520 | 0.6987 | 0.7517 | 0.7242 | 0.9270 |
| 0.0095 | 193.0 | 12545 | 0.5860 | 0.6911 | 0.7614 | 0.7245 | 0.9260 |
| 0.0095 | 194.0 | 12610 | 0.5421 | 0.6837 | 0.7459 | 0.7135 | 0.9264 |
| 0.0095 | 195.0 | 12675 | 0.5621 | 0.6992 | 0.7477 | 0.7227 | 0.9275 |
| 0.0095 | 196.0 | 12740 | 0.5307 | 0.6807 | 0.7610 | 0.7186 | 0.9269 |
| 0.0095 | 197.0 | 12805 | 0.5398 | 0.6901 | 0.7684 | 0.7272 | 0.9291 |
| 0.0095 | 198.0 | 12870 | 0.5218 | 0.7054 | 0.7292 | 0.7171 | 0.9287 |
| 0.0095 | 199.0 | 12935 | 0.5509 | 0.7039 | 0.7454 | 0.7240 | 0.9288 |
| 0.0094 | 200.0 | 13000 | 0.5395 | 0.7091 | 0.7349 | 0.7218 | 0.9280 |
| 0.0094 | 201.0 | 13065 | 0.5347 | 0.6962 | 0.7427 | 0.7187 | 0.9286 |
| 0.0094 | 202.0 | 13130 | 0.5980 | 0.6966 | 0.7560 | 0.7251 | 0.9271 |
| 0.0094 | 203.0 | 13195 | 0.5151 | 0.6984 | 0.7619 | 0.7288 | 0.9292 |
| 0.0094 | 204.0 | 13260 | 0.5244 | 0.7135 | 0.7455 | 0.7292 | 0.9294 |
| 0.0094 | 205.0 | 13325 | 0.5664 | 0.7054 | 0.7475 | 0.7258 | 0.9292 |
| 0.0094 | 206.0 | 13390 | 0.5729 | 0.7006 | 0.7618 | 0.7299 | 0.9295 |
| 0.0094 | 207.0 | 13455 | 0.5834 | 0.6901 | 0.7508 | 0.7192 | 0.9273 |
| 0.0089 | 208.0 | 13520 | 0.5885 | 0.6816 | 0.7841 | 0.7293 | 0.9277 |
| 0.0089 | 209.0 | 13585 | 0.5586 | 0.7052 | 0.7583 | 0.7308 | 0.9281 |
| 0.0089 | 210.0 | 13650 | 0.5871 | 0.7068 | 0.7353 | 0.7207 | 0.9262 |
| 0.0089 | 211.0 | 13715 | 0.5802 | 0.6929 | 0.7704 | 0.7296 | 0.9290 |
| 0.0089 | 212.0 | 13780 | 0.5821 | 0.7031 | 0.7551 | 0.7281 | 0.9286 |
| 0.0089 | 213.0 | 13845 | 0.5787 | 0.6994 | 0.7497 | 0.7237 | 0.9273 |
| 0.0089 | 214.0 | 13910 | 0.5695 | 0.7156 | 0.7389 | 0.7270 | 0.9278 |
| 0.0089 | 215.0 | 13975 | 0.5749 | 0.7095 | 0.7446 | 0.7266 | 0.9284 |
| 0.0083 | 216.0 | 14040 | 0.5886 | 0.7165 | 0.7011 | 0.7087 | 0.9244 |
| 0.0083 | 217.0 | 14105 | 0.5926 | 0.7061 | 0.7497 | 0.7272 | 0.9276 |
| 0.0083 | 218.0 | 14170 | 0.5653 | 0.7020 | 0.7558 | 0.7279 | 0.9284 |
| 0.0083 | 219.0 | 14235 | 0.5784 | 0.6897 | 0.7612 | 0.7237 | 0.9258 |
| 0.0083 | 220.0 | 14300 | 0.5431 | 0.7095 | 0.7452 | 0.7269 | 0.9295 |
| 0.0083 | 221.0 | 14365 | 0.5665 | 0.7175 | 0.7340 | 0.7257 | 0.9284 |
| 0.0083 | 222.0 | 14430 | 0.5842 | 0.6817 | 0.7536 | 0.7159 | 0.9269 |
| 0.0083 | 223.0 | 14495 | 0.5912 | 0.6896 | 0.7634 | 0.7246 | 0.9268 |
| 0.0082 | 224.0 | 14560 | 0.5530 | 0.6944 | 0.7558 | 0.7238 | 0.9281 |
| 0.0082 | 225.0 | 14625 | 0.5632 | 0.6987 | 0.7567 | 0.7265 | 0.9266 |
| 0.0082 | 226.0 | 14690 | 0.5775 | 0.7042 | 0.7536 | 0.7281 | 0.9284 |
| 0.0082 | 227.0 | 14755 | 0.5711 | 0.7029 | 0.7632 | 0.7318 | 0.9283 |
| 0.0082 | 228.0 | 14820 | 0.5421 | 0.7052 | 0.7639 | 0.7334 | 0.9290 |
| 0.0082 | 229.0 | 14885 | 0.5243 | 0.7023 | 0.7400 | 0.7206 | 0.9276 |
| 0.0082 | 230.0 | 14950 | 0.5334 | 0.7236 | 0.7457 | 0.7345 | 0.9304 |
| 0.0077 | 231.0 | 15015 | 0.5182 | 0.7159 | 0.7527 | 0.7338 | 0.9298 |
| 0.0077 | 232.0 | 15080 | 0.5799 | 0.7046 | 0.7533 | 0.7281 | 0.9290 |
| 0.0077 | 233.0 | 15145 | 0.5645 | 0.72 | 0.7358 | 0.7278 | 0.9279 |
| 0.0077 | 234.0 | 15210 | 0.5880 | 0.7043 | 0.7632 | 0.7326 | 0.9287 |
| 0.0077 | 235.0 | 15275 | 0.5719 | 0.7036 | 0.7623 | 0.7318 | 0.9289 |
| 0.0077 | 236.0 | 15340 | 0.5524 | 0.6983 | 0.7560 | 0.7260 | 0.9287 |
| 0.0077 | 237.0 | 15405 | 0.5634 | 0.7138 | 0.7459 | 0.7295 | 0.9299 |
| 0.0077 | 238.0 | 15470 | 0.5849 | 0.7064 | 0.7531 | 0.7290 | 0.9296 |
| 0.0067 | 239.0 | 15535 | 0.5679 | 0.7168 | 0.7554 | 0.7356 | 0.9307 |
| 0.0067 | 240.0 | 15600 | 0.5597 | 0.7112 | 0.7383 | 0.7245 | 0.9276 |
| 0.0067 | 241.0 | 15665 | 0.5438 | 0.7049 | 0.7583 | 0.7306 | 0.9302 |
| 0.0067 | 242.0 | 15730 | 0.5389 | 0.7134 | 0.7715 | 0.7413 | 0.9316 |
| 0.0067 | 243.0 | 15795 | 0.5709 | 0.7042 | 0.7666 | 0.7341 | 0.9295 |
| 0.0067 | 244.0 | 15860 | 0.5667 | 0.7207 | 0.7684 | 0.7438 | 0.9322 |
| 0.0067 | 245.0 | 15925 | 0.5797 | 0.7064 | 0.7785 | 0.7407 | 0.9308 |
| 0.0067 | 246.0 | 15990 | 0.5750 | 0.7058 | 0.7439 | 0.7244 | 0.9301 |
| 0.0057 | 247.0 | 16055 | 0.5512 | 0.7169 | 0.7455 | 0.7309 | 0.9295 |
| 0.0057 | 248.0 | 16120 | 0.5879 | 0.7164 | 0.7581 | 0.7367 | 0.9301 |
| 0.0057 | 249.0 | 16185 | 0.5835 | 0.7005 | 0.7466 | 0.7228 | 0.9283 |
| 0.0057 | 250.0 | 16250 | 0.5995 | 0.7126 | 0.7430 | 0.7275 | 0.9283 |
| 0.0057 | 251.0 | 16315 | 0.5777 | 0.7165 | 0.7452 | 0.7306 | 0.9297 |
| 0.0057 | 252.0 | 16380 | 0.6438 | 0.7095 | 0.7041 | 0.7068 | 0.9237 |
| 0.0057 | 253.0 | 16445 | 0.5909 | 0.7130 | 0.7607 | 0.7361 | 0.9301 |
| 0.0059 | 254.0 | 16510 | 0.5994 | 0.7028 | 0.7735 | 0.7365 | 0.9298 |
| 0.0059 | 255.0 | 16575 | 0.6400 | 0.6955 | 0.7347 | 0.7146 | 0.9259 |
| 0.0059 | 256.0 | 16640 | 0.6058 | 0.7157 | 0.7367 | 0.7261 | 0.9281 |
| 0.0059 | 257.0 | 16705 | 0.5847 | 0.7112 | 0.7445 | 0.7274 | 0.9287 |
| 0.0059 | 258.0 | 16770 | 0.5671 | 0.7093 | 0.7625 | 0.7349 | 0.9293 |
| 0.0059 | 259.0 | 16835 | 0.5933 | 0.7170 | 0.7556 | 0.7358 | 0.9304 |
| 0.0059 | 260.0 | 16900 | 0.6272 | 0.7131 | 0.7664 | 0.7388 | 0.9300 |
| 0.0059 | 261.0 | 16965 | 0.5712 | 0.7160 | 0.7601 | 0.7374 | 0.9304 |
| 0.0053 | 262.0 | 17030 | 0.5971 | 0.7119 | 0.7659 | 0.7379 | 0.9303 |
| 0.0053 | 263.0 | 17095 | 0.6383 | 0.6756 | 0.7657 | 0.7178 | 0.9259 |
| 0.0053 | 264.0 | 17160 | 0.5686 | 0.7032 | 0.7446 | 0.7233 | 0.9283 |
| 0.0053 | 265.0 | 17225 | 0.5792 | 0.7030 | 0.7421 | 0.7220 | 0.9276 |
| 0.0053 | 266.0 | 17290 | 0.6041 | 0.6967 | 0.7637 | 0.7287 | 0.9292 |
| 0.0053 | 267.0 | 17355 | 0.5978 | 0.6912 | 0.7589 | 0.7234 | 0.9269 |
| 0.0053 | 268.0 | 17420 | 0.5909 | 0.7291 | 0.7274 | 0.7282 | 0.9288 |
| 0.0053 | 269.0 | 17485 | 0.5901 | 0.7180 | 0.7275 | 0.7227 | 0.9276 |
| 0.0057 | 270.0 | 17550 | 0.5717 | 0.7172 | 0.7610 | 0.7385 | 0.9320 |
| 0.0057 | 271.0 | 17615 | 0.6098 | 0.6978 | 0.7623 | 0.7286 | 0.9281 |
| 0.0057 | 272.0 | 17680 | 0.5926 | 0.6875 | 0.7729 | 0.7277 | 0.9285 |
| 0.0057 | 273.0 | 17745 | 0.6437 | 0.6875 | 0.7079 | 0.6975 | 0.9209 |
| 0.0057 | 274.0 | 17810 | 0.5944 | 0.7172 | 0.7526 | 0.7344 | 0.9298 |
| 0.0057 | 275.0 | 17875 | 0.5906 | 0.7072 | 0.7549 | 0.7302 | 0.9293 |
| 0.0057 | 276.0 | 17940 | 0.5991 | 0.7186 | 0.7378 | 0.7281 | 0.9292 |
| 0.0056 | 277.0 | 18005 | 0.6014 | 0.7104 | 0.7301 | 0.7201 | 0.9280 |
| 0.0056 | 278.0 | 18070 | 0.6015 | 0.7129 | 0.7464 | 0.7293 | 0.9287 |
| 0.0056 | 279.0 | 18135 | 0.5949 | 0.6951 | 0.7488 | 0.7209 | 0.9270 |
| 0.0056 | 280.0 | 18200 | 0.6075 | 0.7179 | 0.7349 | 0.7263 | 0.9284 |
| 0.0056 | 281.0 | 18265 | 0.6210 | 0.7281 | 0.7436 | 0.7357 | 0.9291 |
| 0.0056 | 282.0 | 18330 | 0.5559 | 0.7056 | 0.7590 | 0.7313 | 0.9298 |
| 0.0056 | 283.0 | 18395 | 0.5862 | 0.7115 | 0.7416 | 0.7262 | 0.9285 |
| 0.0056 | 284.0 | 18460 | 0.5718 | 0.6846 | 0.7549 | 0.7181 | 0.9274 |
| 0.0047 | 285.0 | 18525 | 0.6232 | 0.6974 | 0.7554 | 0.7253 | 0.9298 |
| 0.0047 | 286.0 | 18590 | 0.5914 | 0.7210 | 0.7558 | 0.7380 | 0.9317 |
| 0.0047 | 287.0 | 18655 | 0.5987 | 0.7054 | 0.7691 | 0.7359 | 0.9290 |
| 0.0047 | 288.0 | 18720 | 0.5748 | 0.7158 | 0.7418 | 0.7286 | 0.9291 |
| 0.0047 | 289.0 | 18785 | 0.5806 | 0.7108 | 0.7718 | 0.7401 | 0.9311 |
| 0.0047 | 290.0 | 18850 | 0.5703 | 0.7148 | 0.7493 | 0.7317 | 0.9310 |
| 0.0047 | 291.0 | 18915 | 0.6137 | 0.7129 | 0.7520 | 0.7319 | 0.9289 |
| 0.0047 | 292.0 | 18980 | 0.6269 | 0.6850 | 0.7619 | 0.7214 | 0.9270 |
| 0.0045 | 293.0 | 19045 | 0.6266 | 0.7234 | 0.7497 | 0.7363 | 0.9297 |
| 0.0045 | 294.0 | 19110 | 0.6222 | 0.7090 | 0.7628 | 0.7349 | 0.9297 |
| 0.0045 | 295.0 | 19175 | 0.6219 | 0.7178 | 0.7544 | 0.7356 | 0.9300 |
| 0.0045 | 296.0 | 19240 | 0.6016 | 0.7105 | 0.7452 | 0.7274 | 0.9290 |
| 0.0045 | 297.0 | 19305 | 0.6085 | 0.7182 | 0.7439 | 0.7308 | 0.9281 |
| 0.0045 | 298.0 | 19370 | 0.6173 | 0.7191 | 0.7347 | 0.7268 | 0.9280 |
| 0.0045 | 299.0 | 19435 | 0.6191 | 0.7060 | 0.7699 | 0.7366 | 0.9304 |
| 0.0047 | 300.0 | 19500 | 0.6290 | 0.7084 | 0.7627 | 0.7345 | 0.9286 |
| 0.0047 | 301.0 | 19565 | 0.6393 | 0.7059 | 0.7529 | 0.7287 | 0.9274 |
| 0.0047 | 302.0 | 19630 | 0.6031 | 0.7145 | 0.7603 | 0.7367 | 0.9306 |
| 0.0047 | 303.0 | 19695 | 0.6039 | 0.7164 | 0.7594 | 0.7373 | 0.9297 |
| 0.0047 | 304.0 | 19760 | 0.6030 | 0.7185 | 0.7441 | 0.7311 | 0.9294 |
| 0.0047 | 305.0 | 19825 | 0.5769 | 0.7150 | 0.7603 | 0.7370 | 0.9309 |
| 0.0047 | 306.0 | 19890 | 0.6012 | 0.7246 | 0.7421 | 0.7333 | 0.9300 |
| 0.0047 | 307.0 | 19955 | 0.6078 | 0.7256 | 0.7581 | 0.7415 | 0.9316 |
| 0.0039 | 308.0 | 20020 | 0.6202 | 0.7305 | 0.7319 | 0.7312 | 0.9303 |
| 0.0039 | 309.0 | 20085 | 0.6358 | 0.6995 | 0.7488 | 0.7233 | 0.9275 |
| 0.0039 | 310.0 | 20150 | 0.6055 | 0.7121 | 0.7520 | 0.7315 | 0.9313 |
| 0.0039 | 311.0 | 20215 | 0.6117 | 0.7273 | 0.7735 | 0.7497 | 0.9329 |
| 0.0039 | 312.0 | 20280 | 0.6420 | 0.7171 | 0.7497 | 0.7331 | 0.9304 |
| 0.0039 | 313.0 | 20345 | 0.6377 | 0.7234 | 0.7374 | 0.7303 | 0.9296 |
| 0.0039 | 314.0 | 20410 | 0.6171 | 0.7145 | 0.7684 | 0.7405 | 0.9310 |
| 0.0039 | 315.0 | 20475 | 0.6080 | 0.7198 | 0.7598 | 0.7393 | 0.9309 |
| 0.0029 | 316.0 | 20540 | 0.6138 | 0.7120 | 0.7592 | 0.7349 | 0.9279 |
| 0.0029 | 317.0 | 20605 | 0.6281 | 0.6997 | 0.7590 | 0.7282 | 0.9270 |
| 0.0029 | 318.0 | 20670 | 0.6142 | 0.7268 | 0.7517 | 0.7390 | 0.9305 |
| 0.0029 | 319.0 | 20735 | 0.6059 | 0.7123 | 0.7670 | 0.7386 | 0.9314 |
| 0.0029 | 320.0 | 20800 | 0.6118 | 0.7174 | 0.7607 | 0.7384 | 0.9313 |
| 0.0029 | 321.0 | 20865 | 0.6140 | 0.6964 | 0.7762 | 0.7341 | 0.9308 |
| 0.0029 | 322.0 | 20930 | 0.6255 | 0.7292 | 0.7331 | 0.7311 | 0.9290 |
| 0.0029 | 323.0 | 20995 | 0.6043 | 0.7250 | 0.7473 | 0.7360 | 0.9309 |
| 0.0038 | 324.0 | 21060 | 0.5779 | 0.7095 | 0.7443 | 0.7265 | 0.9301 |
| 0.0038 | 325.0 | 21125 | 0.6084 | 0.7115 | 0.7636 | 0.7366 | 0.9306 |
| 0.0038 | 326.0 | 21190 | 0.6254 | 0.7091 | 0.7376 | 0.7231 | 0.9277 |
| 0.0038 | 327.0 | 21255 | 0.6108 | 0.7133 | 0.7461 | 0.7293 | 0.9293 |
| 0.0038 | 328.0 | 21320 | 0.5968 | 0.7092 | 0.7581 | 0.7329 | 0.9301 |
| 0.0038 | 329.0 | 21385 | 0.6199 | 0.7259 | 0.7430 | 0.7344 | 0.9301 |
| 0.0038 | 330.0 | 21450 | 0.5808 | 0.7177 | 0.7681 | 0.7420 | 0.9317 |
| 0.0034 | 331.0 | 21515 | 0.6018 | 0.7286 | 0.7495 | 0.7389 | 0.9317 |
| 0.0034 | 332.0 | 21580 | 0.5741 | 0.7236 | 0.7677 | 0.7450 | 0.9324 |
| 0.0034 | 333.0 | 21645 | 0.6533 | 0.7171 | 0.7427 | 0.7297 | 0.9278 |
| 0.0034 | 334.0 | 21710 | 0.6345 | 0.7273 | 0.7589 | 0.7428 | 0.9315 |
| 0.0034 | 335.0 | 21775 | 0.6038 | 0.7153 | 0.7634 | 0.7386 | 0.9311 |
| 0.0034 | 336.0 | 21840 | 0.5935 | 0.7169 | 0.7706 | 0.7428 | 0.9319 |
| 0.0034 | 337.0 | 21905 | 0.6395 | 0.7105 | 0.7668 | 0.7376 | 0.9304 |
| 0.0034 | 338.0 | 21970 | 0.6657 | 0.7239 | 0.7654 | 0.7440 | 0.9313 |
| 0.0024 | 339.0 | 22035 | 0.6201 | 0.7219 | 0.7522 | 0.7367 | 0.9312 |
| 0.0024 | 340.0 | 22100 | 0.6169 | 0.7196 | 0.7726 | 0.7451 | 0.9315 |
| 0.0024 | 341.0 | 22165 | 0.6293 | 0.7145 | 0.7652 | 0.7390 | 0.9312 |
| 0.0024 | 342.0 | 22230 | 0.6227 | 0.7079 | 0.7628 | 0.7343 | 0.9295 |
| 0.0024 | 343.0 | 22295 | 0.6166 | 0.7025 | 0.7704 | 0.7349 | 0.9310 |
| 0.0024 | 344.0 | 22360 | 0.6056 | 0.7067 | 0.7650 | 0.7347 | 0.9299 |
| 0.0024 | 345.0 | 22425 | 0.6378 | 0.7161 | 0.7502 | 0.7327 | 0.9298 |
| 0.0024 | 346.0 | 22490 | 0.6221 | 0.7281 | 0.7464 | 0.7372 | 0.9312 |
| 0.0028 | 347.0 | 22555 | 0.6400 | 0.7185 | 0.7560 | 0.7367 | 0.9294 |
| 0.0028 | 348.0 | 22620 | 0.5877 | 0.7114 | 0.7641 | 0.7368 | 0.9310 |
| 0.0028 | 349.0 | 22685 | 0.6571 | 0.7195 | 0.7400 | 0.7296 | 0.9279 |
| 0.0028 | 350.0 | 22750 | 0.6218 | 0.7225 | 0.7672 | 0.7442 | 0.9320 |
| 0.0028 | 351.0 | 22815 | 0.6104 | 0.7167 | 0.7563 | 0.7360 | 0.9300 |
| 0.0028 | 352.0 | 22880 | 0.5932 | 0.7240 | 0.7745 | 0.7484 | 0.9322 |
| 0.0028 | 353.0 | 22945 | 0.6179 | 0.7197 | 0.7654 | 0.7418 | 0.9314 |
| 0.0024 | 354.0 | 23010 | 0.6408 | 0.7186 | 0.7560 | 0.7368 | 0.9300 |
| 0.0024 | 355.0 | 23075 | 0.6872 | 0.7136 | 0.7499 | 0.7313 | 0.9286 |
| 0.0024 | 356.0 | 23140 | 0.6455 | 0.7247 | 0.7632 | 0.7434 | 0.9322 |
| 0.0024 | 357.0 | 23205 | 0.6436 | 0.7252 | 0.7663 | 0.7452 | 0.9321 |
| 0.0024 | 358.0 | 23270 | 0.6535 | 0.7134 | 0.7502 | 0.7313 | 0.9304 |
| 0.0024 | 359.0 | 23335 | 0.6103 | 0.7283 | 0.7558 | 0.7418 | 0.9311 |
| 0.0024 | 360.0 | 23400 | 0.6041 | 0.7110 | 0.7455 | 0.7278 | 0.9285 |
| 0.0024 | 361.0 | 23465 | 0.6251 | 0.7207 | 0.7500 | 0.7351 | 0.9303 |
| 0.0026 | 362.0 | 23530 | 0.6199 | 0.7286 | 0.7450 | 0.7367 | 0.9322 |
| 0.0026 | 363.0 | 23595 | 0.6266 | 0.7169 | 0.7661 | 0.7407 | 0.9318 |
| 0.0026 | 364.0 | 23660 | 0.6309 | 0.7246 | 0.7461 | 0.7352 | 0.9294 |
| 0.0026 | 365.0 | 23725 | 0.6148 | 0.7271 | 0.7551 | 0.7408 | 0.9304 |
| 0.0026 | 366.0 | 23790 | 0.6224 | 0.7174 | 0.7493 | 0.7330 | 0.9292 |
| 0.0026 | 367.0 | 23855 | 0.6127 | 0.7141 | 0.7630 | 0.7378 | 0.9308 |
| 0.0026 | 368.0 | 23920 | 0.5988 | 0.7294 | 0.7596 | 0.7442 | 0.9331 |
| 0.0026 | 369.0 | 23985 | 0.6042 | 0.7344 | 0.7643 | 0.7490 | 0.9338 |
| 0.0025 | 370.0 | 24050 | 0.6340 | 0.7259 | 0.7619 | 0.7435 | 0.9319 |
| 0.0025 | 371.0 | 24115 | 0.6372 | 0.7307 | 0.7650 | 0.7474 | 0.9334 |
| 0.0025 | 372.0 | 24180 | 0.6162 | 0.7089 | 0.7772 | 0.7415 | 0.9313 |
| 0.0025 | 373.0 | 24245 | 0.6779 | 0.7000 | 0.7735 | 0.7349 | 0.9286 |
| 0.0025 | 374.0 | 24310 | 0.6175 | 0.7245 | 0.7681 | 0.7456 | 0.9331 |
| 0.0025 | 375.0 | 24375 | 0.6254 | 0.7218 | 0.7722 | 0.7461 | 0.9325 |
| 0.0025 | 376.0 | 24440 | 0.6425 | 0.7287 | 0.7502 | 0.7393 | 0.9309 |
| 0.0015 | 377.0 | 24505 | 0.6314 | 0.7338 | 0.7495 | 0.7416 | 0.9325 |
| 0.0015 | 378.0 | 24570 | 0.6191 | 0.7149 | 0.7722 | 0.7424 | 0.9312 |
| 0.0015 | 379.0 | 24635 | 0.6438 | 0.7063 | 0.7590 | 0.7317 | 0.9291 |
| 0.0015 | 380.0 | 24700 | 0.6355 | 0.7217 | 0.7616 | 0.7411 | 0.9321 |
| 0.0015 | 381.0 | 24765 | 0.6429 | 0.7204 | 0.7439 | 0.7320 | 0.9303 |
| 0.0015 | 382.0 | 24830 | 0.6409 | 0.7252 | 0.7619 | 0.7431 | 0.9318 |
| 0.0015 | 383.0 | 24895 | 0.6743 | 0.7289 | 0.7423 | 0.7355 | 0.9302 |
| 0.0015 | 384.0 | 24960 | 0.6780 | 0.7181 | 0.7437 | 0.7307 | 0.9287 |
| 0.0017 | 385.0 | 25025 | 0.6480 | 0.7270 | 0.7544 | 0.7404 | 0.9311 |
| 0.0017 | 386.0 | 25090 | 0.6748 | 0.7276 | 0.7277 | 0.7276 | 0.9285 |
| 0.0017 | 387.0 | 25155 | 0.6960 | 0.7143 | 0.7389 | 0.7264 | 0.9279 |
| 0.0017 | 388.0 | 25220 | 0.6537 | 0.7255 | 0.7504 | 0.7377 | 0.9306 |
| 0.0017 | 389.0 | 25285 | 0.7304 | 0.7127 | 0.7545 | 0.7330 | 0.9280 |
| 0.0017 | 390.0 | 25350 | 0.6923 | 0.7113 | 0.7630 | 0.7362 | 0.9291 |
| 0.0017 | 391.0 | 25415 | 0.6787 | 0.7142 | 0.7596 | 0.7362 | 0.9290 |
| 0.0017 | 392.0 | 25480 | 0.7050 | 0.7406 | 0.7236 | 0.7320 | 0.9278 |
| 0.0013 | 393.0 | 25545 | 0.6789 | 0.7280 | 0.7533 | 0.7404 | 0.9308 |
| 0.0013 | 394.0 | 25610 | 0.6330 | 0.7183 | 0.7690 | 0.7427 | 0.9320 |
| 0.0013 | 395.0 | 25675 | 0.6889 | 0.7213 | 0.7536 | 0.7371 | 0.9299 |
| 0.0013 | 396.0 | 25740 | 0.6299 | 0.7184 | 0.7493 | 0.7335 | 0.9307 |
| 0.0013 | 397.0 | 25805 | 0.6603 | 0.7201 | 0.7621 | 0.7405 | 0.9318 |
| 0.0013 | 398.0 | 25870 | 0.7018 | 0.7230 | 0.7229 | 0.7229 | 0.9275 |
| 0.0013 | 399.0 | 25935 | 0.6745 | 0.7075 | 0.7684 | 0.7367 | 0.9299 |
| 0.0015 | 400.0 | 26000 | 0.6466 | 0.7229 | 0.7744 | 0.7478 | 0.9325 |
| 0.0015 | 401.0 | 26065 | 0.6440 | 0.7292 | 0.7612 | 0.7448 | 0.9329 |
| 0.0015 | 402.0 | 26130 | 0.6509 | 0.7219 | 0.7668 | 0.7437 | 0.9313 |
| 0.0015 | 403.0 | 26195 | 0.6519 | 0.7278 | 0.7571 | 0.7422 | 0.9321 |
| 0.0015 | 404.0 | 26260 | 0.6517 | 0.7241 | 0.7715 | 0.7471 | 0.9317 |
| 0.0015 | 405.0 | 26325 | 0.6455 | 0.7224 | 0.7625 | 0.7419 | 0.9323 |
| 0.0015 | 406.0 | 26390 | 0.6664 | 0.7258 | 0.7675 | 0.7461 | 0.9327 |
| 0.0015 | 407.0 | 26455 | 0.7176 | 0.7249 | 0.7556 | 0.7400 | 0.9297 |
| 0.0012 | 408.0 | 26520 | 0.6886 | 0.7287 | 0.7599 | 0.7440 | 0.9312 |
| 0.0012 | 409.0 | 26585 | 0.6968 | 0.7172 | 0.7513 | 0.7339 | 0.9290 |
| 0.0012 | 410.0 | 26650 | 0.6707 | 0.7260 | 0.7511 | 0.7384 | 0.9309 |
| 0.0012 | 411.0 | 26715 | 0.7018 | 0.7320 | 0.7448 | 0.7384 | 0.9299 |
| 0.0012 | 412.0 | 26780 | 0.6798 | 0.7234 | 0.7587 | 0.7406 | 0.9316 |
| 0.0012 | 413.0 | 26845 | 0.6907 | 0.7160 | 0.7652 | 0.7398 | 0.9303 |
| 0.0012 | 414.0 | 26910 | 0.6880 | 0.7211 | 0.7538 | 0.7371 | 0.9307 |
| 0.0012 | 415.0 | 26975 | 0.6796 | 0.7155 | 0.7536 | 0.7341 | 0.9302 |
| 0.0009 | 416.0 | 27040 | 0.6835 | 0.7220 | 0.7567 | 0.7389 | 0.9309 |
| 0.0009 | 417.0 | 27105 | 0.6773 | 0.7058 | 0.7646 | 0.7340 | 0.9300 |
| 0.0009 | 418.0 | 27170 | 0.6562 | 0.7199 | 0.7684 | 0.7434 | 0.9317 |
| 0.0009 | 419.0 | 27235 | 0.6718 | 0.7220 | 0.7664 | 0.7435 | 0.9321 |
| 0.0009 | 420.0 | 27300 | 0.6761 | 0.7246 | 0.7585 | 0.7412 | 0.9311 |
| 0.0009 | 421.0 | 27365 | 0.6712 | 0.7298 | 0.7659 | 0.7474 | 0.9314 |
| 0.0009 | 422.0 | 27430 | 0.6811 | 0.7302 | 0.7618 | 0.7456 | 0.9309 |
| 0.0009 | 423.0 | 27495 | 0.6950 | 0.7252 | 0.7544 | 0.7395 | 0.9301 |
| 0.0007 | 424.0 | 27560 | 0.7030 | 0.7259 | 0.7627 | 0.7438 | 0.9310 |
| 0.0007 | 425.0 | 27625 | 0.7093 | 0.7064 | 0.7769 | 0.7400 | 0.9294 |
| 0.0007 | 426.0 | 27690 | 0.7105 | 0.7333 | 0.7562 | 0.7446 | 0.9308 |
| 0.0007 | 427.0 | 27755 | 0.7196 | 0.7178 | 0.7789 | 0.7471 | 0.9307 |
| 0.0007 | 428.0 | 27820 | 0.6914 | 0.7217 | 0.7682 | 0.7442 | 0.9314 |
| 0.0007 | 429.0 | 27885 | 0.6860 | 0.7259 | 0.7601 | 0.7426 | 0.9305 |
| 0.0007 | 430.0 | 27950 | 0.6911 | 0.7207 | 0.7722 | 0.7455 | 0.9313 |
| 0.0008 | 431.0 | 28015 | 0.7007 | 0.7286 | 0.7526 | 0.7404 | 0.9299 |
| 0.0008 | 432.0 | 28080 | 0.7129 | 0.7198 | 0.7504 | 0.7348 | 0.9291 |
| 0.0008 | 433.0 | 28145 | 0.6910 | 0.7298 | 0.7569 | 0.7431 | 0.9311 |
| 0.0008 | 434.0 | 28210 | 0.7067 | 0.7208 | 0.7639 | 0.7417 | 0.9298 |
| 0.0008 | 435.0 | 28275 | 0.6896 | 0.7278 | 0.7549 | 0.7411 | 0.9315 |
| 0.0008 | 436.0 | 28340 | 0.7031 | 0.7208 | 0.7749 | 0.7469 | 0.9319 |
| 0.0008 | 437.0 | 28405 | 0.7314 | 0.7204 | 0.7590 | 0.7392 | 0.9297 |
| 0.0008 | 438.0 | 28470 | 0.6934 | 0.7300 | 0.7522 | 0.7409 | 0.9310 |
| 0.0007 | 439.0 | 28535 | 0.7172 | 0.7358 | 0.7392 | 0.7375 | 0.9297 |
| 0.0007 | 440.0 | 28600 | 0.6985 | 0.7287 | 0.7621 | 0.7450 | 0.9313 |
| 0.0007 | 441.0 | 28665 | 0.6903 | 0.7293 | 0.7572 | 0.7430 | 0.9311 |
| 0.0007 | 442.0 | 28730 | 0.6720 | 0.7358 | 0.7599 | 0.7477 | 0.9323 |
| 0.0007 | 443.0 | 28795 | 0.6941 | 0.7353 | 0.7418 | 0.7385 | 0.9304 |
| 0.0007 | 444.0 | 28860 | 0.6800 | 0.7283 | 0.7695 | 0.7483 | 0.9324 |
| 0.0007 | 445.0 | 28925 | 0.6815 | 0.7337 | 0.7639 | 0.7485 | 0.9322 |
| 0.0007 | 446.0 | 28990 | 0.6668 | 0.7249 | 0.7549 | 0.7396 | 0.9311 |
| 0.0008 | 447.0 | 29055 | 0.6607 | 0.7273 | 0.7646 | 0.7455 | 0.9328 |
| 0.0008 | 448.0 | 29120 | 0.7068 | 0.7249 | 0.7661 | 0.7449 | 0.9314 |
| 0.0008 | 449.0 | 29185 | 0.6863 | 0.7221 | 0.7645 | 0.7427 | 0.9312 |
| 0.0008 | 450.0 | 29250 | 0.6756 | 0.7197 | 0.7627 | 0.7406 | 0.9308 |
| 0.0008 | 451.0 | 29315 | 0.6713 | 0.7146 | 0.7708 | 0.7416 | 0.9313 |
| 0.0008 | 452.0 | 29380 | 0.6752 | 0.7307 | 0.7515 | 0.7409 | 0.9303 |
| 0.0008 | 453.0 | 29445 | 0.6649 | 0.7253 | 0.7585 | 0.7415 | 0.9316 |
| 0.0007 | 454.0 | 29510 | 0.6674 | 0.7242 | 0.7686 | 0.7458 | 0.9321 |
| 0.0007 | 455.0 | 29575 | 0.6737 | 0.7309 | 0.7599 | 0.7451 | 0.9316 |
| 0.0007 | 456.0 | 29640 | 0.6754 | 0.7242 | 0.7697 | 0.7462 | 0.9321 |
| 0.0007 | 457.0 | 29705 | 0.6835 | 0.7263 | 0.7585 | 0.7421 | 0.9309 |
| 0.0007 | 458.0 | 29770 | 0.6787 | 0.7277 | 0.7614 | 0.7442 | 0.9319 |
| 0.0007 | 459.0 | 29835 | 0.6670 | 0.7303 | 0.7655 | 0.7475 | 0.9324 |
| 0.0007 | 460.0 | 29900 | 0.6763 | 0.7294 | 0.7585 | 0.7436 | 0.9312 |
| 0.0007 | 461.0 | 29965 | 0.6675 | 0.7286 | 0.7637 | 0.7457 | 0.9326 |
| 0.0004 | 462.0 | 30030 | 0.6649 | 0.7225 | 0.7657 | 0.7435 | 0.9323 |
| 0.0004 | 463.0 | 30095 | 0.6520 | 0.7309 | 0.7607 | 0.7455 | 0.9324 |
| 0.0004 | 464.0 | 30160 | 0.6608 | 0.7285 | 0.7614 | 0.7446 | 0.9322 |
| 0.0004 | 465.0 | 30225 | 0.6873 | 0.7329 | 0.7486 | 0.7407 | 0.9301 |
| 0.0004 | 466.0 | 30290 | 0.6809 | 0.7276 | 0.7646 | 0.7456 | 0.9317 |
| 0.0004 | 467.0 | 30355 | 0.6843 | 0.7306 | 0.7614 | 0.7457 | 0.9316 |
| 0.0004 | 468.0 | 30420 | 0.6933 | 0.7332 | 0.7603 | 0.7465 | 0.9314 |
| 0.0004 | 469.0 | 30485 | 0.6982 | 0.7360 | 0.7571 | 0.7464 | 0.9311 |
| 0.0004 | 470.0 | 30550 | 0.7029 | 0.7274 | 0.7596 | 0.7431 | 0.9308 |
| 0.0004 | 471.0 | 30615 | 0.6756 | 0.7305 | 0.7699 | 0.7497 | 0.9330 |
| 0.0004 | 472.0 | 30680 | 0.6885 | 0.7241 | 0.7664 | 0.7446 | 0.9315 |
| 0.0004 | 473.0 | 30745 | 0.6867 | 0.7277 | 0.7581 | 0.7426 | 0.9310 |
| 0.0004 | 474.0 | 30810 | 0.6772 | 0.7264 | 0.7679 | 0.7466 | 0.9321 |
| 0.0004 | 475.0 | 30875 | 0.6808 | 0.7246 | 0.7753 | 0.7491 | 0.9321 |
| 0.0004 | 476.0 | 30940 | 0.6808 | 0.7239 | 0.7673 | 0.7450 | 0.9318 |
| 0.0004 | 477.0 | 31005 | 0.6904 | 0.7275 | 0.7601 | 0.7435 | 0.9314 |
| 0.0004 | 478.0 | 31070 | 0.6921 | 0.7269 | 0.7598 | 0.7430 | 0.9312 |
| 0.0004 | 479.0 | 31135 | 0.6927 | 0.7261 | 0.7654 | 0.7452 | 0.9315 |
| 0.0004 | 480.0 | 31200 | 0.6969 | 0.7262 | 0.7641 | 0.7446 | 0.9316 |
| 0.0004 | 481.0 | 31265 | 0.7027 | 0.7287 | 0.7576 | 0.7429 | 0.9313 |
| 0.0004 | 482.0 | 31330 | 0.7015 | 0.7269 | 0.7601 | 0.7431 | 0.9313 |
| 0.0004 | 483.0 | 31395 | 0.6975 | 0.7271 | 0.7596 | 0.7430 | 0.9314 |
| 0.0004 | 484.0 | 31460 | 0.6970 | 0.7247 | 0.7648 | 0.7442 | 0.9315 |
| 0.0002 | 485.0 | 31525 | 0.6991 | 0.7257 | 0.7612 | 0.7430 | 0.9312 |
| 0.0002 | 486.0 | 31590 | 0.6969 | 0.7274 | 0.7619 | 0.7442 | 0.9314 |
| 0.0002 | 487.0 | 31655 | 0.7045 | 0.7200 | 0.7599 | 0.7394 | 0.9306 |
| 0.0002 | 488.0 | 31720 | 0.7049 | 0.7221 | 0.7627 | 0.7418 | 0.9309 |
| 0.0002 | 489.0 | 31785 | 0.7044 | 0.7242 | 0.7643 | 0.7437 | 0.9313 |
| 0.0002 | 490.0 | 31850 | 0.7011 | 0.7254 | 0.7650 | 0.7447 | 0.9318 |
| 0.0002 | 491.0 | 31915 | 0.7045 | 0.7252 | 0.7634 | 0.7438 | 0.9316 |
| 0.0002 | 492.0 | 31980 | 0.7050 | 0.7262 | 0.7603 | 0.7429 | 0.9314 |
| 0.0003 | 493.0 | 32045 | 0.7061 | 0.7266 | 0.7623 | 0.7440 | 0.9316 |
| 0.0003 | 494.0 | 32110 | 0.7075 | 0.7253 | 0.7599 | 0.7422 | 0.9314 |
| 0.0003 | 495.0 | 32175 | 0.7079 | 0.7266 | 0.7601 | 0.7430 | 0.9314 |
| 0.0003 | 496.0 | 32240 | 0.7072 | 0.7267 | 0.7594 | 0.7427 | 0.9314 |
| 0.0003 | 497.0 | 32305 | 0.7074 | 0.7265 | 0.7598 | 0.7428 | 0.9314 |
| 0.0003 | 498.0 | 32370 | 0.7093 | 0.7261 | 0.7590 | 0.7422 | 0.9311 |
| 0.0003 | 499.0 | 32435 | 0.7083 | 0.7270 | 0.7596 | 0.7429 | 0.9313 |
| 0.0002 | 500.0 | 32500 | 0.7082 | 0.7269 | 0.7596 | 0.7429 | 0.9313 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
|
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prajwalJumde/mrr_class_test_07_08
|
prajwalJumde
| 2023-12-14T12:32:18Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:32:18Z |
Entry not found
|
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guipiveti/distilbert-base-uncased-finetuned
|
guipiveti
| 2023-12-14T12:32:43Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:32:43Z |
Entry not found
|
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BrianHsu/my_awesome_swag_model
|
BrianHsu
| 2023-12-14T12:32:54Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:32:54Z |
Entry not found
|
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] |
kanishka/smolm-autoreg-bpe-counterfactual-babylm-indef_articles_with_pl_nouns-removal-1e-4
|
kanishka
| 2023-12-15T01:53:36Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"opt",
"text-generation",
"generated_from_trainer",
"dataset:kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal",
"model-index",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] |
text-generation
| 2023-12-14T12:33:02Z |
---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-indef_articles_with_pl_nouns-removal-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
type: kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.40685132585936323
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smolm-autoreg-bpe-counterfactual-babylm-indef_articles_with_pl_nouns-removal-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4203
- Accuracy: 0.4069
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 32000
- num_epochs: 20.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0459 | 1.0 | 18601 | 4.2512 | 0.3119 |
| 3.5647 | 2.0 | 37202 | 3.7353 | 0.3623 |
| 3.3872 | 3.0 | 55803 | 3.5881 | 0.3793 |
| 3.2888 | 4.0 | 74404 | 3.5327 | 0.3882 |
| 3.2221 | 5.0 | 93005 | 3.4746 | 0.3931 |
| 3.1699 | 6.0 | 111606 | 3.4427 | 0.3965 |
| 3.1314 | 7.0 | 130207 | 3.4235 | 0.3991 |
| 3.0928 | 8.0 | 148808 | 3.4092 | 0.4010 |
| 3.0595 | 9.0 | 167409 | 3.4074 | 0.4025 |
| 3.0344 | 10.0 | 186010 | 3.4222 | 0.4023 |
| 3.0028 | 11.0 | 204611 | 3.4034 | 0.4043 |
| 2.9831 | 12.0 | 223212 | 3.4022 | 0.4043 |
| 2.9626 | 13.0 | 241813 | 3.4060 | 0.4054 |
| 2.9442 | 14.0 | 260414 | 3.4008 | 0.4060 |
| 2.9257 | 15.0 | 279015 | 3.4016 | 0.4065 |
| 2.909 | 16.0 | 297616 | 3.4037 | 0.4065 |
| 2.8892 | 17.0 | 316217 | 3.4125 | 0.4063 |
| 2.872 | 18.0 | 334818 | 3.4132 | 0.4066 |
| 2.8568 | 19.0 | 353419 | 3.4158 | 0.4069 |
| 2.8385 | 20.0 | 372020 | 3.4203 | 0.4069 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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kiru1998/finetuning-inpainting-diffusion-for-skin-treat
|
kiru1998
| 2023-12-14T12:33:15Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T12:33:15Z |
---
license: apache-2.0
---
|
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versae/norwegian-mistral-7b
|
versae
| 2023-12-14T12:33:33Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:33:33Z |
Entry not found
|
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KaytTech/mistral-7b-dv-finetuned
|
KaytTech
| 2023-12-14T12:37:22Z | 0 | 0 | null |
[
"safetensors",
"autotrain",
"text-generation",
"license:other",
"region:us"
] |
text-generation
| 2023-12-14T12:37:15Z |
---
tags:
- autotrain
- text-generation
widget:
- text: "I love AutoTrain because "
license: other
---
# Model Trained Using AutoTrain
This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
# Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_path = "PATH_TO_THIS_REPO"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(
model_path,
device_map="auto",
torch_dtype='auto'
).eval()
# Prompt content: "hi"
messages = [
{"role": "user", "content": "hi"}
]
input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
output_ids = model.generate(input_ids.to('cuda'))
response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
# Model response: "Hello! How can I assist you today?"
print(response)
```
|
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VidiaOilHungary/VidiaOilHungary
|
VidiaOilHungary
| 2023-12-14T12:42:17Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:37:32Z |
Vidia Oil: Hungary, vélemények, Előnyök, Ár, Hozzávalók, Mellékhatások, művek, Költség!
Vidia Oil Vásárolj most!! További információért kattintson az alábbi linkre, és most 50% kedvezményt kap! siess !!
Olvass tovább: https://www.boxdrug.com/VidOilHung
➢Termék neve – Vidia Oil
➢Kategória – Hallás
➢Fő előnyei – hallástámogatás férfiak és nők számára
➢ Összetétel – természetes szerves vegyület
➢ Mellékhatások – NA
➢Végső értékelés: — 4.8
➢ Elérhetőség — Online
➢Ajánlatok és kedvezmények; MENTESEN MEG! VÁSÁRLÁS MOST AZ AKCIÓS AJÁNLATHOZ!!!
Mi az Vidia Oil?
Érdekli a hallása javítása? Ha igen, akkor az Vidia Oil -et fontolgathatja. Ez a termék olyan összetevőkből áll, amelyekről kimutatták, hogy más hasonló termékekben is működnek, és az ígéretek szerint akár 50%-kal javítja hallását. Vannak azonban lehetséges mellékhatások, amelyekkel tisztában kell lennie.
Vidia Oil Vásárolj most!! További információért kattintson az alábbi linkre, és most 50% kedvezményt kap! siess !!
Olvass tovább: https://www.boxdrug.com/VidOilHung
Vidia Oil Vidia Oil Ár Vidia Oil vélemények Vidia Oil Hozzávalók Vidia Oil Előnyök Vidia Oil Mellékhatások Vidia Oil fogalmazás Vidia Oil panasz Vidia Oil Hol kapható Vidia Oil Hogyan kell használni Vidia Oil Költség Vidia Oil művek Vidia Oil fórum Vidia Oil eredeti Vidia Oil gyógyszertár
https://www.boxdrug.com/VidOilHung
https://sites.google.com/view/vidia-oil-hungary/home
https://healthtoned.blogspot.com/2023/12/vidia-oil-hungary.html
https://www.weddingwire.com/website/vidia-oil-and-hungary
https://medium.com/@healthytalk24x7/vidia-oil-hungary-5ba5950bbc39
https://medium.com/@healthytalk24x7/vidia-oil-hungary-v%C3%A9lem%C3%A9nyek-el%C5%91ny%C3%B6k-%C3%A1r-hozz%C3%A1val%C3%B3k-mell%C3%A9khat%C3%A1sok-m%C5%B1vek-k%C3%B6lts%C3%A9g-99aec18368f6
https://infogram.com/vidia-oil-hungary-1h1749vpq3drl6z?live
https://softisenilspain.hashnode.dev/vidia-oil-hungary
https://vidiaoilhungary.company.site/
https://sway.office.com/dxkAqgHgKRGTGNj7
https://gamma.app/docs/Vidia-Oil-Hungary-v9kjzknutws27vw?mode=doc
https://healthytalk24x7.wixsite.com/sunshine/post/vidia-oil-hungary
https://groups.google.com/g/snshine/c/msgelK9MeVg
https://www.sunflower-cissp.com/glossary/cissp/7243/vidia-oil-hungary
https://community.thebatraanumerology.com/post/vidia-oil-hungary-657af576d12e8dc1bda4560f
https://community.thebatraanumerology.com/user/vidiaoilhungary
https://nepal.tribe.so/post/vidia-oil-hungary-657af6459880ab7e2a43ccec
https://enkling.com/read-blog/8912
https://replit.com/@vidiaoilhungary
|
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] |
sobikim/videomae-base-finetuned-ucf101-subset
|
sobikim
| 2023-12-14T12:53:55Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"videomae",
"video-classification",
"generated_from_trainer",
"base_model:MCG-NJU/videomae-base",
"license:cc-by-nc-4.0",
"endpoints_compatible",
"region:us"
] |
video-classification
| 2023-12-14T12:39:17Z |
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1349
- Accuracy: 0.9857
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7786 | 0.25 | 75 | 1.5436 | 0.4571 |
| 0.5562 | 1.25 | 150 | 0.5586 | 0.7857 |
| 0.3559 | 2.25 | 225 | 0.2251 | 0.9714 |
| 0.0655 | 3.25 | 300 | 0.1349 | 0.9857 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.12.1
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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owanr/ghc-roberta-base-intra-data-frequency-model_annots
|
owanr
| 2023-12-14T13:58:15Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:roberta-base",
"license:mit",
"region:us"
] | null | 2023-12-14T12:39:34Z |
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: ghc-roberta-base-intra-data-frequency-model_annots
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# ghc-roberta-base-intra-data-frequency-model_annots
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 31.6587
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 13.1538 | 1.0 | 345 | 31.2607 |
| 10.6115 | 2.0 | 690 | 31.0756 |
| 10.7235 | 3.0 | 1035 | 31.2023 |
| 14.2731 | 4.0 | 1380 | 31.6587 |
| 9.8347 | 5.0 | 1725 | 31.6587 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|
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Nad1011/Viet-Laos-Translator
|
Nad1011
| 2023-12-15T00:24:29Z | 0 | 0 | null |
[
"translation",
"en",
"vi",
"lo",
"license:unknown",
"region:us"
] |
translation
| 2023-12-14T12:41:01Z |
---
license: unknown
language:
- en
- vi
- lo
metrics:
- bleu
pipeline_tag: translation
---
|
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alitolga/deberta-v3-base-peft
|
alitolga
| 2023-12-17T21:19:05Z | 0 | 0 | null |
[
"safetensors",
"generated_from_trainer",
"base_model:microsoft/deberta-v3-base",
"license:mit",
"region:us"
] | null | 2023-12-14T12:41:10Z |
---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-base-peft
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-v3-base-peft
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8971
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 9.6045 | 1.0 | 258 | 5.7917 |
| 4.3948 | 2.0 | 516 | 3.4037 |
| 3.771 | 3.0 | 774 | 2.8971 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
|
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AdnanRiaz107/codebertmlm1-finetuned-the-stack-bash
|
AdnanRiaz107
| 2023-12-14T12:41:46Z | 0 | 0 | null |
[
"region:us"
] | null | 2023-12-14T12:41:46Z |
Entry not found
|
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] |
zhaoguoffy/uie_senta_mini_pytorch
|
zhaoguoffy
| 2023-12-14T12:45:31Z | 0 | 0 | null |
[
"license:apache-2.0",
"region:us"
] | null | 2023-12-14T12:45:31Z |
---
license: apache-2.0
---
|
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] |
TheAntiChristy/test1
|
TheAntiChristy
| 2023-12-14T12:46:20Z | 0 | 0 | null |
[
"doi:10.57967/hf/1480",
"region:us"
] | null | 2023-12-14T12:46:20Z |
Entry not found
|
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SrPrieto/q-FrozenLake-v1-4x4-Slippery
|
SrPrieto
| 2023-12-14T12:47:02Z | 0 | 0 | null |
[
"FrozenLake-v1-slippery-4x4",
"q-learning",
"reinforcement-learning",
"custom-implementation",
"model-index",
"region:us"
] |
reinforcement-learning
| 2023-12-14T12:46:59Z |
---
tags:
- FrozenLake-v1-slippery-4x4
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: q-FrozenLake-v1-4x4-Slippery
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: FrozenLake-v1-slippery-4x4
type: FrozenLake-v1-slippery-4x4
metrics:
- type: mean_reward
value: 0.67 +/- 0.47
name: mean_reward
verified: false
---
# **Q-Learning** Agent playing1 **FrozenLake-v1-slippery**
This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1-slippery** .
## Usage
```python
model = load_from_hub(repo_id="SrPrieto/q-FrozenLake-v1-4x4-Slippery", filename="q-learning.pkl")
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
```
|
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