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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-tiny-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-tiny-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: 0.5204081632653061 |
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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-tiny-ar-ft-kws-speech-commands |
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This model is a fine-tuned version of [arbml/whisper-tiny-ar](https://huggingface.co/arbml/whisper-tiny-ar) on the Speech Commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8423 |
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- Accuracy: 0.5204 |
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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-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 0.1 |
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- num_epochs: 10 |
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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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| 0.6826 | 1.0 | 1325 | 0.7084 | 0.4966 | |
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| 0.7052 | 2.0 | 2650 | 0.6965 | 0.5 | |
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| 0.7409 | 3.0 | 3975 | 0.6876 | 0.5510 | |
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| 0.7077 | 4.0 | 5300 | 0.7214 | 0.5170 | |
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| 0.7988 | 5.0 | 6625 | 0.7523 | 0.4898 | |
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| 0.5818 | 6.0 | 7950 | 0.8118 | 0.5510 | |
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| 0.7722 | 7.0 | 9275 | 0.9102 | 0.5306 | |
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| 1.4165 | 8.0 | 10600 | 1.6832 | 0.5 | |
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| 0.7113 | 9.0 | 11925 | 1.6268 | 0.5340 | |
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| 0.2578 | 10.0 | 13250 | 1.8423 | 0.5204 | |
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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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