End of training
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- pytorch_model.bin +1 -1
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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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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:
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- eval_batch_size:
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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:
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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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### Framework versions
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- Transformers 4.
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.0
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9
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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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6062
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- Accuracy: 0.9
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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: 8
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- eval_batch_size: 8
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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: 15
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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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| 2.0776 | 1.0 | 113 | 1.9082 | 0.48 |
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| 1.3768 | 2.0 | 226 | 1.3052 | 0.63 |
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| 1.0741 | 3.0 | 339 | 0.9721 | 0.79 |
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| 0.778 | 4.0 | 452 | 0.8452 | 0.76 |
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| 0.6383 | 5.0 | 565 | 0.5935 | 0.85 |
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| 0.3313 | 6.0 | 678 | 0.5947 | 0.81 |
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| 0.3514 | 7.0 | 791 | 0.6064 | 0.8 |
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| 0.0922 | 8.0 | 904 | 0.5759 | 0.81 |
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| 0.1757 | 9.0 | 1017 | 0.4683 | 0.88 |
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| 0.0496 | 10.0 | 1130 | 0.5958 | 0.86 |
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| 0.0141 | 11.0 | 1243 | 0.5512 | 0.87 |
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| 0.0345 | 12.0 | 1356 | 0.6297 | 0.86 |
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| 0.0079 | 13.0 | 1469 | 0.6009 | 0.89 |
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| 0.0072 | 14.0 | 1582 | 0.6069 | 0.9 |
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| 0.007 | 15.0 | 1695 | 0.6062 | 0.9 |
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### Framework versions
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- Transformers 4.35.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.0
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pytorch_model.bin
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