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--- |
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language: |
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- fa |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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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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- mozilla-foundation/common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Persian Iranian |
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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: mozilla-foundation/common_voice_16_0 fa |
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type: mozilla-foundation/common_voice_16_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: 58.59649122807018 |
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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 Persian Iranian |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 fa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7142 |
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- Wer: 58.5965 |
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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: 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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| 1.1086 | 1.02 | 500 | 1.2735 | 85.9444 | |
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| 0.8782 | 3.0 | 1000 | 1.0477 | 76.5527 | |
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| 0.6726 | 4.02 | 1500 | 0.9506 | 71.8807 | |
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| 0.7501 | 6.0 | 2000 | 0.8943 | 69.3890 | |
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| 0.6079 | 7.02 | 2500 | 0.8550 | 67.1322 | |
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| 0.6592 | 9.0 | 3000 | 0.8239 | 66.2762 | |
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| 0.5703 | 10.02 | 3500 | 0.8007 | 63.9907 | |
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| 0.5767 | 12.0 | 4000 | 0.7815 | 63.2562 | |
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| 0.5098 | 13.02 | 4500 | 0.7671 | 62.1094 | |
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| 0.5373 | 15.01 | 5000 | 0.7555 | 61.5551 | |
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| 0.4592 | 16.02 | 5500 | 0.7460 | 61.1086 | |
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| 0.5032 | 18.01 | 6000 | 0.7376 | 60.5652 | |
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| 0.4262 | 19.02 | 6500 | 0.7329 | 60.0792 | |
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| 0.4726 | 21.01 | 7000 | 0.7257 | 59.6696 | |
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| 0.4043 | 22.02 | 7500 | 0.7237 | 59.3570 | |
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| 0.4758 | 24.01 | 8000 | 0.7187 | 59.1098 | |
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| 0.412 | 25.02 | 8500 | 0.7173 | 58.8518 | |
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| 0.5119 | 27.01 | 9000 | 0.7146 | 58.7276 | |
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| 0.4089 | 28.03 | 9500 | 0.7145 | 58.6347 | |
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| 0.5186 | 30.01 | 10000 | 0.7142 | 58.5965 | |
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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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