File size: 1,837 Bytes
48c0b96
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: testing_pretrained_niger_mali
  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. -->

# testing_pretrained_niger_mali

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9245
- Wer: 0.8889

## 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: 3e-05
- 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: 350

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.427         | 35.29  | 300  | 2.9588          | 1.0    |
| 2.8653        | 70.59  | 600  | 2.7466          | 1.0    |
| 2.7675        | 105.88 | 900  | 2.7207          | 1.0    |
| 2.6674        | 141.18 | 1200 | 2.2285          | 1.0    |
| 1.7813        | 176.47 | 1500 | 1.5717          | 0.8852 |
| 1.0447        | 211.76 | 1800 | 1.7009          | 0.8778 |
| 0.8167        | 247.06 | 2100 | 1.8010          | 0.8815 |
| 0.7059        | 282.35 | 2400 | 1.8748          | 0.8815 |
| 0.6572        | 317.65 | 2700 | 1.9245          | 0.8889 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3