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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: ntu-spml/distilhubert
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - marsyas/gtzan
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: music-classifier-genre-finetuned-gtzan
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: GTZAN
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+ type: marsyas/gtzan
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+ config: all
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+ split: train
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+ args: all
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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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+
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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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+
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+ # music-classifier-genre-finetuned-gtzan
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+
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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: 0.8145
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+ - Accuracy: 0.83
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 4
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+ - eval_batch_size: 4
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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: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.9096 | 1.0 | 225 | 1.7239 | 0.49 |
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+ | 1.056 | 2.0 | 450 | 1.1898 | 0.66 |
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+ | 0.5824 | 3.0 | 675 | 0.7905 | 0.74 |
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+ | 0.2286 | 4.0 | 900 | 0.7436 | 0.8 |
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+ | 0.3129 | 5.0 | 1125 | 0.5656 | 0.84 |
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+ | 0.046 | 6.0 | 1350 | 0.6575 | 0.83 |
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+ | 0.1413 | 7.0 | 1575 | 0.6421 | 0.83 |
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+ | 0.0208 | 8.0 | 1800 | 0.8335 | 0.84 |
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+ | 0.0088 | 9.0 | 2025 | 0.8039 | 0.85 |
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+ | 0.0087 | 10.0 | 2250 | 0.8145 | 0.83 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.0.dev0
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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