File size: 1,851 Bytes
c2de8e2
 
 
 
 
 
62cefe5
c2de8e2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cuad
base_model: google/bert_uncased_L-4_H-512_A-8
model-index:
- name: bert-small-finetuned-cuad-longer
  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-small-finetuned-cuad-longer

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the cuad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0617

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0601        | 1.0   | 8702  | 0.0404          |
| 0.0551        | 2.0   | 17404 | 0.0394          |
| 0.0428        | 3.0   | 26106 | 0.0481          |
| 0.0375        | 4.0   | 34808 | 0.0425          |
| 0.0403        | 5.0   | 43510 | 0.0551          |
| 0.0246        | 6.0   | 52212 | 0.0588          |
| 0.0284        | 7.0   | 60914 | 0.0557          |
| 0.0303        | 8.0   | 69616 | 0.0543          |
| 0.0239        | 9.0   | 78318 | 0.0634          |
| 0.0207        | 10.0  | 87020 | 0.0617          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1