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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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+ base_model: leamac51
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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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+ - f1
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+ model-index:
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+ - name: bsclass-finetuned-gtzan-1st-aprox-less-LR
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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: 0.915
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+ - name: F1
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+ type: f1
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+ value: 0.9147312393158322
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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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+ # bsclass-finetuned-gtzan-1st-aprox-less-LR
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+
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+ This model is a fine-tuned version of [leamac51](https://huggingface.co/leamac51) on the GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5240
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+ - Accuracy: 0.915
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+ - F1: 0.9147
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 2.0897 | 1.0 | 100 | 2.0161 | 0.685 | 0.6827 |
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+ | 1.6456 | 2.0 | 200 | 1.7330 | 0.66 | 0.6290 |
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+ | 1.4091 | 3.0 | 300 | 1.3255 | 0.78 | 0.7732 |
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+ | 1.1217 | 4.0 | 400 | 1.1425 | 0.82 | 0.8186 |
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+ | 1.0118 | 5.0 | 500 | 0.9657 | 0.85 | 0.8524 |
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+ | 0.7186 | 6.0 | 600 | 0.7777 | 0.86 | 0.8609 |
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+ | 0.4308 | 7.0 | 700 | 0.5975 | 0.905 | 0.9040 |
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+ | 0.451 | 8.0 | 800 | 0.5240 | 0.915 | 0.9147 |
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+ | 0.3558 | 9.0 | 900 | 0.5822 | 0.885 | 0.8853 |
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+ | 0.2556 | 10.0 | 1000 | 0.5207 | 0.905 | 0.9052 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
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