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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: openai/whisper-base.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: whisper-base.en-speech-commands-v1 |
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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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# whisper-base.en-speech-commands-v1 |
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the speech_commands dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1638 |
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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: 96 |
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- eval_batch_size: 96 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 384 |
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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: 5 |
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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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| 0.3306 | 1.0 | 103 | 1.1388 | 0.8022 | |
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| 0.1314 | 2.0 | 206 | 1.1511 | 0.8022 | |
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| 0.0672 | 3.0 | 309 | 1.1448 | 0.8062 | |
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| 0.048 | 4.0 | 412 | 1.1638 | 0.8067 | |
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| 0.034 | 5.0 | 515 | 1.1655 | 0.8058 | |
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### Framework versions |
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- Transformers 4.51.2 |
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- Pytorch 2.6.0+cu126 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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