File size: 1,855 Bytes
ba30f2a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f6d7a97
 
ba30f2a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7df0d42
95032a5
ed61774
ba30f2a
f6d7a97
 
ba30f2a
97d1eb3
f6d7a97
ba30f2a
 
 
 
 
f6d7a97
 
 
 
 
ba30f2a
 
 
 
 
 
 
 
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
---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: modernbert_agree_classifier
  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. -->

# modernbert_agree_classifier

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7135
- Accuracy: 0.6114

## 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: 6.000000000000001e-05
- train_batch_size: 6
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 60
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- training_steps: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 6.6012        | 0.2994 | 20   | 0.6613          | 0.6114   |
| 5.841         | 0.5988 | 40   | 0.7060          | 0.6114   |
| 7.3284        | 0.8982 | 60   | 0.6671          | 0.6114   |
| 6.9088        | 1.2096 | 80   | 0.6861          | 0.4834   |
| 7.1679        | 1.5090 | 100  | 0.7135          | 0.6114   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1