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--- |
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license: apache-2.0 |
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base_model: biodatlab/whisper-th-small-combined |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-small-thai |
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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: common_voice_17_0 |
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type: common_voice_17_0 |
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config: th |
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split: test |
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args: th |
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metrics: |
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- name: Wer |
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type: wer |
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value: 55.432891743610334 |
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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-small-thai |
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This model is a fine-tuned version of [biodatlab/whisper-th-small-combined](https://huggingface.co/biodatlab/whisper-th-small-combined) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1073 |
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- Wer: 55.4329 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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| 0.3415 | 0.3647 | 1000 | 0.1371 | 65.4958 | |
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| 0.1638 | 0.7294 | 2000 | 0.1253 | 60.3238 | |
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| 0.1995 | 1.0941 | 3000 | 0.1161 | 57.4736 | |
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| 0.213 | 1.4588 | 4000 | 0.1104 | 56.2358 | |
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| 0.2041 | 1.8235 | 5000 | 0.1073 | 55.4329 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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