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--- |
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license: apache-2.0 |
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base_model: arun100/whisper-base-th-1 |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Thai (2) |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: google/fleurs th_th |
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type: google/fleurs |
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config: th_th |
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split: test |
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args: th_th |
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metrics: |
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- name: Wer |
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type: wer |
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value: 53.662828506943114 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Base Thai (2) |
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This model is a fine-tuned version of [arun100/whisper-base-th-1](https://huggingface.co/arun100/whisper-base-th-1) on the google/fleurs th_th dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5628 |
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- Wer: 53.6628 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-07 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.5011 | 35.0 | 500 | 0.5963 | 59.8868 | |
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| 0.3648 | 71.0 | 1000 | 0.5613 | 55.9542 | |
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| 0.2732 | 107.0 | 1500 | 0.5504 | 54.4585 | |
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| 0.2081 | 142.0 | 2000 | 0.5502 | 53.6705 | |
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| 0.1627 | 178.0 | 2500 | 0.5558 | 53.8273 | |
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| 0.133 | 214.0 | 3000 | 0.5628 | 53.6628 | |
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| 0.1112 | 249.0 | 3500 | 0.5696 | 54.0798 | |
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| 0.0973 | 285.0 | 4000 | 0.5749 | 53.9995 | |
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| 0.0906 | 321.0 | 4500 | 0.5783 | 54.1487 | |
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| 0.0874 | 357.0 | 5000 | 0.5793 | 54.2290 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.2.dev0 |
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- Tokenizers 0.15.0 |
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