File size: 2,023 Bytes
55b1714
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
71
72
73
---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-khmer-aug-v6
  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. -->

# whisper-base-khmer-aug-v6

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2379
- Wer: 62.5101

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- 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: constant
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5956        | 0.9994 | 837  | 0.2717          | 78.0931 |
| 0.2404        | 2.0    | 1675 | 0.2206          | 79.6660 |
| 0.184         | 2.9994 | 2512 | 0.2061          | 68.4287 |
| 0.1511        | 4.0    | 3350 | 0.2001          | 66.4505 |
| 0.1288        | 4.9994 | 4187 | 0.2038          | 66.2883 |
| 0.1108        | 6.0    | 5025 | 0.2032          | 64.6506 |
| 0.0968        | 6.9994 | 5862 | 0.2098          | 64.0182 |
| 0.0842        | 8.0    | 6700 | 0.2180          | 63.5966 |
| 0.0739        | 8.9994 | 7537 | 0.2303          | 63.9857 |
| 0.065         | 9.9940 | 8370 | 0.2379          | 62.5101 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.19.1