File size: 2,225 Bytes
8486ab9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: bert-reg-biencoder-mae
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-reg-biencoder-mae
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2343
- Mse: 0.0824
- Mae: 0.2338
- Pearson Corr: 0.2477
- Spearman Corr: 0.1374
- Cosine Sim: 0.9022
## 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Pearson Corr | Spearman Corr | Cosine Sim |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:|
| 0.2846 | 1.0 | 21 | 0.2617 | 0.1153 | 0.2610 | 0.1327 | 0.0936 | 0.9053 |
| 0.2728 | 2.0 | 42 | 0.2310 | 0.0886 | 0.2304 | 0.0188 | 0.0316 | 0.8994 |
| 0.2511 | 3.0 | 63 | 0.2282 | 0.0847 | 0.2276 | 0.1716 | 0.1111 | 0.9058 |
| 0.2253 | 4.0 | 84 | 0.2333 | 0.0864 | 0.2329 | 0.1906 | 0.1191 | 0.9041 |
| 0.1993 | 5.0 | 105 | 0.2329 | 0.0822 | 0.2326 | 0.2299 | 0.1213 | 0.9016 |
| 0.1845 | 6.0 | 126 | 0.2357 | 0.0829 | 0.2353 | 0.2268 | 0.1254 | 0.9017 |
| 0.165 | 7.0 | 147 | 0.2343 | 0.0824 | 0.2338 | 0.2477 | 0.1374 | 0.9022 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
|