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--- |
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library_name: transformers |
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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-base |
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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 - BH |
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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 - BH |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0151 |
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- Wer: 17.8284 |
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- Cer: 5.3577 |
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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: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 7 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:-------:|:---------------:|:-------:| |
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| 0.0425 | 0.3011 | 400 | 11.2952 | 0.0330 | 37.6901 | |
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| 0.0258 | 0.6023 | 800 | 7.9539 | 0.0218 | 25.4742 | |
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| 0.0197 | 0.9034 | 1200 | 7.0188 | 0.0194 | 22.3362 | |
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| 0.0083 | 1.2637 | 1600 | 6.1604 | 0.0183 | 20.2225 | |
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| 0.0066 | 1.5794 | 2000 | 5.9469 | 0.0176 | 19.4205 | |
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| 0.0065 | 1.8952 | 2400 | 5.8609 | 0.0174 | 19.0958 | |
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| 0.0161 | 2.1084 | 2800 | 5.8786 | 0.0167 | 18.8094 | |
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| 0.0157 | 2.4096 | 3200 | 5.6719 | 0.0162 | 18.4526 | |
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| 0.0157 | 2.7107 | 3600 | 5.6150 | 0.0160 | 18.3772 | |
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| 0.0063 | 3.1595 | 4000 | 5.4820 | 0.0160 | 18.0877 | |
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| 0.0052 | 3.4752 | 4400 | 5.4747 | 0.0161 | 18.2023 | |
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| 0.0049 | 3.7910 | 4800 | 5.5285 | 0.0161 | 17.9922 | |
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| 0.0154 | 3.9155 | 5200 | 5.5457 | 0.0159 | 18.1641 | |
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| 0.0142 | 4.2168 | 5600 | 5.4871 | 0.0158 | 17.9721 | |
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| 0.0143 | 4.5180 | 6000 | 5.5382 | 0.0157 | 18.0495 | |
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| 0.0155 | 4.8191 | 6400 | 5.4620 | 0.0156 | 17.9460 | |
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| 0.005 | 5.3710 | 6800 | 5.4875 | 0.0157 | 17.7691 | |
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| 0.0052 | 5.6868 | 7200 | 5.4416 | 0.0157 | 17.8646 | |
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| 0.0085 | 4.8653 | 7600 | 5.5002 | 0.0157 | 17.8817 | |
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| 0.0096 | 5.1216 | 8000 | 5.5124 | 0.0156 | 17.8264 | |
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| 0.0094 | 5.3776 | 8400 | 5.6387 | 0.0155 | 17.7500 | |
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| 0.0093 | 5.6336 | 8800 | 5.4429 | 0.0154 | 17.6736 | |
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| 0.01 | 5.8896 | 9200 | 5.3128 | 0.0153 | 17.2856 | |
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| 0.0091 | 6.1453 | 9600 | 5.2836 | 0.0153 | 17.2424 | |
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| 0.0088 | 6.4019 | 10000 | 0.0153 | 17.2434 | 5.2826 | |
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| 0.008 | 6.6579 | 10400 | 0.0153 | 17.1288 | 5.2957 | |
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| 0.007 | 6.9139 | 10800 | 0.0153 | 17.1680 | 5.2889 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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