End of training
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README.md
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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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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should probably proofread and complete it, then remove this comment. -->
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# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of [gnuevo/distilhubert-finetuned-gtzan](https://huggingface.co/gnuevo/distilhubert-finetuned-gtzan) 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.
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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metrics:
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- accuracy
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model-index:
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- name: distilhubert-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.83
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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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+
# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of [gnuevo/distilhubert-finetuned-gtzan](https://huggingface.co/gnuevo/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6408
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- Accuracy: 0.83
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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: 5e-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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- 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: 0.15
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.2638 | 1.0 | 57 | 2.2585 | 0.17 |
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| 1.9343 | 2.0 | 114 | 1.9475 | 0.6 |
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| 1.2679 | 3.0 | 171 | 1.4426 | 0.7 |
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| 0.6692 | 4.0 | 228 | 1.0634 | 0.74 |
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| 0.4132 | 5.0 | 285 | 0.8203 | 0.82 |
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| 0.188 | 6.0 | 342 | 0.6990 | 0.85 |
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| 0.1295 | 7.0 | 399 | 0.6518 | 0.83 |
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| 0.2153 | 8.0 | 456 | 0.6430 | 0.84 |
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| 0.1812 | 9.0 | 513 | 0.6403 | 0.83 |
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| 0.3722 | 10.0 | 570 | 0.6408 | 0.83 |
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### Framework versions
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model.safetensors
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size 95463244
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