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--- |
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library_name: transformers |
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language: |
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- am |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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: ' tiny Amharic - Biniyam Daniel' |
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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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# tiny Amharic - Biniyam Daniel |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0803 |
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- Wer: 24.4366 |
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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 OptimizerNames.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_ratio: 0.1 |
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- num_epochs: 2 |
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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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| 1.5795 | 0.0665 | 100 | 1.5182 | 150.6407 | |
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| 1.2873 | 0.1330 | 200 | 1.2244 | 109.2797 | |
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| 0.3664 | 0.1995 | 300 | 0.3282 | 70.2607 | |
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| 0.2133 | 0.2660 | 400 | 0.2056 | 52.2095 | |
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| 0.171 | 0.3324 | 500 | 0.1731 | 46.8184 | |
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| 0.1422 | 0.3989 | 600 | 0.1467 | 41.7587 | |
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| 0.1392 | 0.4654 | 700 | 0.1344 | 38.8643 | |
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| 0.1264 | 0.5319 | 800 | 0.1247 | 36.7654 | |
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| 0.1113 | 0.5984 | 900 | 0.1186 | 34.3570 | |
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| 0.1038 | 0.6649 | 1000 | 0.1125 | 33.0977 | |
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| 0.0978 | 0.7314 | 1100 | 0.1091 | 33.0535 | |
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| 0.0959 | 0.7979 | 1200 | 0.1033 | 30.3137 | |
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| 0.0876 | 0.8644 | 1300 | 0.1003 | 29.6730 | |
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| 0.0975 | 0.9309 | 1400 | 0.0966 | 29.6730 | |
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| 0.0863 | 0.9973 | 1500 | 0.0968 | 28.9660 | |
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| 0.0633 | 1.0638 | 1600 | 0.0934 | 28.0601 | |
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| 0.0612 | 1.1303 | 1700 | 0.0913 | 28.3031 | |
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| 0.0576 | 1.1968 | 1800 | 0.0905 | 27.1542 | |
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| 0.0652 | 1.2633 | 1900 | 0.0886 | 27.1984 | |
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| 0.0636 | 1.3298 | 2000 | 0.0857 | 26.5135 | |
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| 0.0623 | 1.3963 | 2100 | 0.0852 | 25.9611 | |
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| 0.0556 | 1.4628 | 2200 | 0.0839 | 25.3646 | |
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| 0.0569 | 1.5293 | 2300 | 0.0827 | 25.6739 | |
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| 0.0574 | 1.5957 | 2400 | 0.0822 | 25.2762 | |
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| 0.0649 | 1.6622 | 2500 | 0.0813 | 24.9448 | |
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| 0.0744 | 1.7287 | 2600 | 0.0808 | 24.7238 | |
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| 0.0686 | 1.7952 | 2700 | 0.0805 | 24.7017 | |
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| 0.0587 | 1.8617 | 2800 | 0.0803 | 24.4145 | |
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| 0.0615 | 1.9282 | 2900 | 0.0803 | 24.4366 | |
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| 0.0637 | 1.9947 | 3000 | 0.0803 | 24.4366 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.22.1 |
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