File size: 1,820 Bytes
dd2ead2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f0e7200
 
dd2ead2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f0e7200
dd2ead2
 
 
f0e7200
 
 
 
 
 
 
 
 
 
 
 
dd2ead2
 
 
 
 
 
 
 
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
---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased
  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. -->

# distilbert-base-uncased

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3188
- Accuracy: 0.9224

## 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: 4
- seed: 1010
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.104         | 1.0   | 2370  | 0.1172          | 0.9724   |
| 0.143         | 2.0   | 4740  | 0.1707          | 0.9608   |
| 0.2895        | 3.0   | 7110  | 0.3216          | 0.9224   |
| 0.3122        | 4.0   | 9480  | 0.3178          | 0.9224   |
| 0.3177        | 5.0   | 11850 | 0.3223          | 0.9224   |
| 0.318         | 6.0   | 14220 | 0.3182          | 0.9224   |
| 0.3174        | 7.0   | 16590 | 0.3194          | 0.9224   |
| 0.317         | 8.0   | 18960 | 0.3183          | 0.9224   |
| 0.3176        | 9.0   | 21330 | 0.3179          | 0.9224   |
| 0.3178        | 10.0  | 23700 | 0.3188          | 0.9224   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1