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--- |
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language: |
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- ar |
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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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- mozilla-foundation/common_voice_11_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small ar - younes matrab |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: ar |
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split: None |
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args: 'config: ar, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 61.65413533834586 |
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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 ar - younes matrab |
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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 11.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8027 |
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- Wer: 61.6541 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 4 |
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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: 100 |
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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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| 1.7188 | 0.4167 | 10 | 2.7773 | 67.1053 | |
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| 1.6979 | 0.8333 | 20 | 2.4033 | 66.5414 | |
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| 1.3932 | 1.25 | 30 | 1.9422 | 66.3534 | |
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| 1.0467 | 1.6667 | 40 | 1.6225 | 65.2256 | |
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| 0.8824 | 2.0833 | 50 | 1.3586 | 64.4737 | |
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| 0.5935 | 2.5 | 60 | 1.0915 | 62.4060 | |
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| 0.4491 | 2.9167 | 70 | 0.8986 | 63.3459 | |
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| 0.3438 | 3.3333 | 80 | 0.8473 | 61.6541 | |
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| 0.2915 | 3.75 | 90 | 0.8132 | 60.1504 | |
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| 0.2391 | 4.1667 | 100 | 0.8027 | 61.6541 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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