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--- |
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license: apache-2.0 |
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base_model: arun100/whisper-base-vi-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 Vietnamese |
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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 vi_vn |
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type: google/fleurs |
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config: vi_vn |
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split: test |
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args: vi_vn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 31.03382013835511 |
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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 Vietnamese |
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This model is a fine-tuned version of [arun100/whisper-base-vi-1](https://huggingface.co/arun100/whisper-base-vi-1) on the google/fleurs vi_vn dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6949 |
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- Wer: 31.0338 |
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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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| 0.5823 | 43.0 | 500 | 0.7964 | 37.8978 | |
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| 0.3312 | 86.0 | 1000 | 0.6997 | 33.7125 | |
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| 0.2009 | 130.0 | 1500 | 0.6784 | 32.7479 | |
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| 0.1271 | 173.0 | 2000 | 0.6760 | 31.9985 | |
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| 0.0815 | 217.0 | 2500 | 0.6799 | 31.3028 | |
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| 0.0561 | 260.0 | 3000 | 0.6851 | 31.2337 | |
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| 0.0438 | 304.0 | 3500 | 0.6896 | 31.7256 | |
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| 0.0367 | 347.0 | 4000 | 0.6928 | 31.5949 | |
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| 0.0331 | 391.0 | 4500 | 0.6949 | 31.0338 | |
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| 0.0317 | 434.0 | 5000 | 0.6957 | 31.0453 | |
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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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