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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: arbml/whisper-small-ar |
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tags: |
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- generated_from_trainer |
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datasets: |
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- speech_commands |
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metrics: |
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- accuracy |
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model-index: |
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- name: whisper-small-ar-ft-kws-speech-commands |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: Speech Commands |
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type: speech_commands |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5748299319727891 |
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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-ft-kws-speech-commands |
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This model is a fine-tuned version of [arbml/whisper-small-ar](https://huggingface.co/arbml/whisper-small-ar) on the Speech Commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.3471 |
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- Accuracy: 0.5748 |
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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-06 |
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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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- 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: linear |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 20 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.682 | 1.0 | 166 | 0.6867 | 0.6395 | |
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| 0.6463 | 2.0 | 332 | 0.6377 | 0.6531 | |
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| 0.5829 | 3.0 | 498 | 0.6250 | 0.6633 | |
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| 0.6197 | 4.0 | 664 | 0.6798 | 0.6429 | |
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| 0.3921 | 5.0 | 830 | 0.9584 | 0.5918 | |
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| 0.3009 | 6.0 | 996 | 0.9658 | 0.6395 | |
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| 0.123 | 7.0 | 1162 | 1.3115 | 0.6293 | |
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| 0.1418 | 8.0 | 1328 | 1.8621 | 0.6190 | |
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| 0.1181 | 9.0 | 1494 | 2.2151 | 0.6020 | |
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| 0.0014 | 10.0 | 1660 | 2.3968 | 0.6156 | |
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| 0.0007 | 11.0 | 1826 | 2.7913 | 0.5646 | |
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| 0.0004 | 12.0 | 1992 | 2.9198 | 0.6020 | |
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| 0.0003 | 13.0 | 2158 | 2.9664 | 0.5850 | |
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| 0.0002 | 14.0 | 2324 | 3.1507 | 0.5850 | |
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| 0.0002 | 15.0 | 2490 | 3.1987 | 0.5884 | |
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| 0.0001 | 16.0 | 2656 | 3.2650 | 0.5782 | |
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| 0.0001 | 17.0 | 2822 | 3.3091 | 0.5714 | |
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| 0.0002 | 18.0 | 2988 | 3.3048 | 0.5782 | |
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| 0.0023 | 19.0 | 3154 | 3.2925 | 0.5918 | |
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| 0.0001 | 20.0 | 3320 | 3.3471 | 0.5748 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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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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