File size: 1,852 Bytes
dec5df7
 
 
bb4c23d
 
dec5df7
 
 
 
 
 
 
 
 
 
 
 
6794870
 
 
dec5df7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6794870
 
 
 
 
 
 
 
dec5df7
 
 
 
bb4c23d
 
6794870
bb4c23d
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
70
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Model_G_S_P_Wav2Vec2
  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. -->

# Model_G_S_P_Wav2Vec2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5098
- Wer: 0.5366
- Cer: 0.2277

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.0449        | 3.49  | 400  | 1.7576          | 0.6270 | 0.2607 |
| 0.484         | 6.99  | 800  | 1.8072          | 0.6043 | 0.2536 |
| 0.3335        | 10.48 | 1200 | 2.0222          | 0.5892 | 0.2500 |
| 0.2559        | 13.97 | 1600 | 2.4174          | 0.5719 | 0.2448 |
| 0.1999        | 17.47 | 2000 | 2.2888          | 0.5566 | 0.2376 |
| 0.1546        | 20.96 | 2400 | 2.5271          | 0.5753 | 0.2400 |
| 0.1225        | 24.45 | 2800 | 2.4489          | 0.5427 | 0.2327 |
| 0.0983        | 27.95 | 3200 | 2.5098          | 0.5366 | 0.2277 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3