tensorops commited on
Commit
54b5aea
1 Parent(s): 13db2e6

add new model

Browse files
README.md CHANGED
@@ -10,13 +10,13 @@ datasets:
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  metrics:
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  - wer
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  model-index:
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- - name: Whisper Small Th Additional Data - biodatlab
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  results:
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  - task:
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  name: Automatic Speech Recognition
17
  type: automatic-speech-recognition
18
  dataset:
19
- name: Common Voice 11.0
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  type: mozilla-foundation/common_voice_11_0
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  config: th
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  split: test
@@ -24,18 +24,18 @@ model-index:
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  metrics:
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  - name: Wer
26
  type: wer
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- value: 62.71786878276888
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  ---
29
 
30
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
31
  should probably proofread and complete it, then remove this comment. -->
32
 
33
- # Whisper Small Th Additional Data - biodatlab
34
 
35
- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
36
  It achieves the following results on the evaluation set:
37
- - Loss: 0.1986
38
- - Wer: 62.7179
39
 
40
  ## Model description
41
 
@@ -55,31 +55,25 @@ More information needed
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56
  The following hyperparameters were used during training:
57
  - learning_rate: 1e-05
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- - train_batch_size: 32
59
- - eval_batch_size: 8
60
  - seed: 42
61
- - gradient_accumulation_steps: 2
62
- - total_train_batch_size: 64
63
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
64
  - lr_scheduler_type: linear
65
  - lr_scheduler_warmup_steps: 500
66
  - training_steps: 5000
67
- - mixed_precision_training: Native AMP
68
 
69
  ### Training results
70
 
71
  | Training Loss | Epoch | Step | Validation Loss | Wer |
72
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
73
- | 0.3104 | 1.46 | 1000 | 0.1969 | 67.1036 |
74
- | 0.2026 | 2.93 | 2000 | 0.1686 | 63.4264 |
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- | 0.0975 | 4.39 | 3000 | 0.1780 | 61.8818 |
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- | 0.0591 | 5.86 | 4000 | 0.1877 | 62.6045 |
77
- | 0.0328 | 7.32 | 5000 | 0.1986 | 62.7179 |
78
 
79
 
80
  ### Framework versions
81
 
82
- - Transformers 4.26.0.dev0
83
- - Pytorch 1.13.0
84
- - Datasets 2.7.1
85
  - Tokenizers 0.13.2
 
10
  metrics:
11
  - wer
12
  model-index:
13
+ - name: Whisper Small Thai Combined Concat
14
  results:
15
  - task:
16
  name: Automatic Speech Recognition
17
  type: automatic-speech-recognition
18
  dataset:
19
+ name: mozilla-foundation/common_voice_11_0 th
20
  type: mozilla-foundation/common_voice_11_0
21
  config: th
22
  split: test
 
24
  metrics:
25
  - name: Wer
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  type: wer
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+ value: 27.279438445464898
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  ---
29
 
30
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
31
  should probably proofread and complete it, then remove this comment. -->
32
 
33
+ # Whisper Small Thai Combined Concat
34
 
35
+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 th dataset and additional scraped data.
36
  It achieves the following results on the evaluation set:
37
+ - Loss: 0.5034
38
+ - Wer: 27.2794 (without tokenizer)
39
 
40
  ## Model description
41
 
 
55
 
56
  The following hyperparameters were used during training:
57
  - learning_rate: 1e-05
58
+ - train_batch_size: 64
59
+ - eval_batch_size: 32
60
  - seed: 42
61
+ - distributed_type: multi-GPU
 
62
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
63
  - lr_scheduler_type: linear
64
  - lr_scheduler_warmup_steps: 500
65
  - training_steps: 5000
 
66
 
67
  ### Training results
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Wer |
70
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
71
+ | 0.0002 | 83.33 | 5000 | 0.5034 | 27.2794 |
 
 
 
 
72
 
73
 
74
  ### Framework versions
75
 
76
+ - Transformers 4.27.0.dev0
77
+ - Pytorch 1.13.1
78
+ - Datasets 2.9.1.dev0
79
  - Tokenizers 0.13.2
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