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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-base-ar-quran |
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results: [] |
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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-ar-quran |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None 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: 5.7544 |
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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: 0.0001 |
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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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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 128 |
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- total_eval_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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| 0.1092 | 0.05 | 250 | 0.1969 | 13.3890 | |
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| 0.0361 | 0.1 | 500 | 0.1583 | 10.6375 | |
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| 0.0192 | 0.15 | 750 | 0.1109 | 8.8468 | |
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| 0.0144 | 0.2 | 1000 | 0.1157 | 7.9754 | |
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| 0.008 | 0.25 | 1250 | 0.1000 | 7.5360 | |
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| 0.0048 | 1.03 | 1500 | 0.0933 | 6.8227 | |
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| 0.0113 | 1.08 | 1750 | 0.0955 | 6.9638 | |
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| 0.0209 | 1.13 | 2000 | 0.0824 | 6.3586 | |
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| 0.0043 | 1.18 | 2250 | 0.0830 | 6.3444 | |
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| 0.002 | 1.23 | 2500 | 0.1015 | 6.3025 | |
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| 0.0013 | 2.01 | 2750 | 0.0863 | 6.0639 | |
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| 0.0014 | 2.06 | 3000 | 0.0905 | 6.0213 | |
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| 0.0018 | 2.11 | 3250 | 0.0864 | 6.0293 | |
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| 0.0008 | 2.16 | 3500 | 0.0887 | 5.9308 | |
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| 0.0029 | 2.21 | 3750 | 0.0777 | 5.9159 | |
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| 0.0022 | 2.26 | 4000 | 0.0847 | 5.8749 | |
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| 0.0005 | 3.05 | 4250 | 0.0827 | 5.8352 | |
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| 0.0003 | 3.1 | 4500 | 0.0826 | 5.7800 | |
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| 0.0006 | 3.15 | 4750 | 0.0833 | 5.7625 | |
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| 0.0003 | 3.2 | 5000 | 0.0839 | 5.7544 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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