End of training
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README.md
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This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.9651
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- Recall: 0.9481
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- F1: 0.9476
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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:
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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 | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 0.
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| 0.0055 | 5.0 | 565 | 0.2165 | 0.9651 | 0.9481 | 0.9476 |
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### Framework versions
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This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1933
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- Precision: 0.9651
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- Recall: 0.9481
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- F1: 0.9476
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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: 4
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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 | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 0.3705 | 1.0 | 113 | 0.2441 | 0.9566 | 0.9434 | 0.9432 |
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| 0.1728 | 2.0 | 226 | 0.1617 | 0.9608 | 0.9481 | 0.9478 |
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| 0.0321 | 3.0 | 339 | 0.1838 | 0.9651 | 0.9481 | 0.9476 |
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| 0.011 | 4.0 | 452 | 0.1933 | 0.9651 | 0.9481 | 0.9476 |
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### Framework versions
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model.safetensors
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