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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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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-fa |
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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: fa |
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split: test |
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args: fa |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.497333642476235 |
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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-fa |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.9258 |
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- Wer: 35.4973 |
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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: 16 |
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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: 100000 |
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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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| 0.0193 | 8.1103 | 20000 | 0.5349 | 36.7125 | |
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| 0.0046 | 16.2206 | 40000 | 0.6839 | 36.0033 | |
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| 0.0018 | 24.3309 | 60000 | 0.7936 | 36.2543 | |
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| 0.0003 | 32.4412 | 80000 | 0.8729 | 35.9406 | |
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| 0.0 | 40.5515 | 100000 | 0.9258 | 35.4973 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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