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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- 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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| 0.0537 | 5.98 | 169 | 0.6066 | 0.84 |
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| 0.0422 | 6.97 | 197 | 0.5947 | 0.84 |
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| 0.0422 | 8.0 | 226 | 0.5898 | 0.85 |
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| 0.0415 | 8.99 | 254 | 0.6020 | 0.85 |
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| 0.0296 | 9.91 | 280 | 0.6339 | 0.85 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.
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- Tokenizers 0.13.3
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.67
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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: 1.2964
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- Accuracy: 0.67
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## Model description
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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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| 2.1699 | 0.99 | 28 | 2.0590 | 0.44 |
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| 1.8177 | 1.98 | 56 | 1.6737 | 0.56 |
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| 1.5311 | 2.97 | 84 | 1.4527 | 0.64 |
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| 1.4022 | 4.0 | 113 | 1.3283 | 0.69 |
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| 1.3342 | 4.96 | 140 | 1.2964 | 0.67 |
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### Framework versions
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- Transformers 4.32.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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pytorch_model.bin
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