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--- |
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library_name: transformers |
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language: |
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- fa |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/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-large-v3-turbo-fa - Sadegh Karimi |
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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: mozilla-foundation/common_voice_17_0 |
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config: fa |
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split: test |
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args: 'config: hi, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 9.627528266117483 |
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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-large-v3-turbo-fa - Sadegh Karimi |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) 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: 0.0839 |
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- Wer: 9.6275 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 10000 |
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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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| 0.1789 | 0.0217 | 500 | 0.2427 | 26.4099 | |
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| 0.2077 | 0.0435 | 1000 | 0.2296 | 27.1873 | |
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| 0.1928 | 0.0652 | 1500 | 0.2320 | 27.5951 | |
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| 0.1801 | 0.0869 | 2000 | 0.2026 | 24.0409 | |
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| 0.1865 | 0.1086 | 2500 | 0.1925 | 22.3742 | |
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| 0.1535 | 0.1304 | 3000 | 0.1872 | 22.9511 | |
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| 0.1463 | 0.1521 | 3500 | 0.1786 | 21.5436 | |
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| 0.0935 | 0.1738 | 4000 | 0.1749 | 20.5330 | |
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| 0.1052 | 0.1956 | 4500 | 0.1597 | 19.0314 | |
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| 0.091 | 0.2173 | 5000 | 0.1553 | 20.2125 | |
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| 0.0743 | 0.2390 | 5500 | 0.1474 | 16.9160 | |
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| 0.096 | 0.2607 | 6000 | 0.1352 | 15.9027 | |
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| 0.111 | 0.2825 | 6500 | 0.1259 | 14.9071 | |
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| 0.089 | 0.3042 | 7000 | 0.1179 | 14.1146 | |
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| 0.0813 | 0.3259 | 7500 | 0.1101 | 12.8653 | |
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| 0.072 | 0.3477 | 8000 | 0.1012 | 11.8138 | |
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| 0.0715 | 0.3694 | 8500 | 0.0948 | 10.9791 | |
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| 0.0683 | 0.3911 | 9000 | 0.0903 | 10.2563 | |
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| 0.0634 | 0.4128 | 9500 | 0.0861 | 9.6616 | |
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| 0.0739 | 0.4346 | 10000 | 0.0839 | 9.6275 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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