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--- |
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license: mit |
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base_model: distil-whisper/distil-small.en |
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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: distil-small.en-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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config: v0.02 |
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split: None |
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args: v0.02 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8066546762589928 |
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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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# distil-small.en-speech-commands |
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This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9307 |
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- Accuracy: 0.8067 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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_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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| 0.1861 | 1.0 | 618 | 0.7743 | 0.8022 | |
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| 0.1135 | 2.0 | 1236 | 0.9853 | 0.8049 | |
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| 0.078 | 3.0 | 1854 | 0.9307 | 0.8067 | |
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| 0.038 | 4.0 | 2472 | 0.9989 | 0.8049 | |
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| 0.0375 | 5.0 | 3090 | 1.0738 | 0.8035 | |
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| 0.0462 | 6.0 | 3708 | 1.1601 | 0.8067 | |
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| 0.018 | 7.0 | 4326 | 1.5369 | 0.8067 | |
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| 0.0008 | 8.0 | 4944 | 1.2515 | 0.8067 | |
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| 0.0016 | 9.0 | 5562 | 1.3494 | 0.8058 | |
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| 0.0002 | 10.0 | 6180 | 1.5117 | 0.8053 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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