davidggphy
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update model card README.md
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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: 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:
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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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| 0.0893 | 6.0 | 342 | 0.4645 | 0.86 |
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| 0.0075 | 7.0 | 399 | 0.4542 | 0.87 |
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| 0.0704 | 8.0 | 456 | 0.5085 | 0.87 |
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| 0.0034 | 9.0 | 513 | 0.4899 | 0.88 |
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| 0.0031 | 10.0 | 570 | 0.4814 | 0.86 |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.87
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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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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4853
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- Accuracy: 0.87
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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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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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 5
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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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| 0.0028 | 0.98 | 28 | 0.4659 | 0.88 |
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| 0.0197 | 2.0 | 57 | 0.4713 | 0.9 |
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| 0.019 | 2.98 | 85 | 0.5138 | 0.9 |
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| 0.0133 | 4.0 | 114 | 0.4830 | 0.88 |
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| 0.0117 | 4.91 | 140 | 0.4853 | 0.87 |
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### Framework versions
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