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README.md
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license: apache-2.0
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base_model:
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tags:
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- generated_from_trainer
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datasets:
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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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# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of [
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+
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- Datasets 2.14.
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- Tokenizers 0.13.3
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---
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license: apache-2.0
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base_model: weiren119/distilhubert-finetuned-finetuned-gtzan
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.88
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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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# distilhubert-finetuned-gtzan
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This model is a fine-tuned version of [weiren119/distilhubert-finetuned-finetuned-gtzan](https://huggingface.co/weiren119/distilhubert-finetuned-finetuned-gtzan) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9411
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- Accuracy: 0.88
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0012 | 1.0 | 57 | 0.9231 | 0.86 |
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| 0.0009 | 2.0 | 114 | 0.9304 | 0.88 |
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| 0.0007 | 3.0 | 171 | 0.9359 | 0.87 |
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| 0.0008 | 4.0 | 228 | 1.0345 | 0.85 |
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| 0.0007 | 5.0 | 285 | 0.9492 | 0.87 |
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| 0.0139 | 6.0 | 342 | 0.9883 | 0.86 |
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| 0.0409 | 7.0 | 399 | 0.9377 | 0.88 |
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| 0.0005 | 8.0 | 456 | 0.9460 | 0.88 |
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| 0.0005 | 9.0 | 513 | 0.9462 | 0.88 |
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| 0.0005 | 10.0 | 570 | 0.9411 | 0.88 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.1
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- Tokenizers 0.13.3
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