| --- |
| library_name: transformers |
| base_model: leamac51 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - marsyas/gtzan |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: bsclass-finetuned-gtzan-1st-aprox-less-LR |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: GTZAN |
| type: marsyas/gtzan |
| config: all |
| split: train |
| args: all |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.915 |
| - name: F1 |
| type: f1 |
| value: 0.9147312393158322 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # bsclass-finetuned-gtzan-1st-aprox-less-LR |
|
|
| This model is a fine-tuned version of [leamac51](https://huggingface.co/leamac51) on the GTZAN dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5240 |
| - Accuracy: 0.915 |
| - F1: 0.9147 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 2.0897 | 1.0 | 100 | 2.0161 | 0.685 | 0.6827 | |
| | 1.6456 | 2.0 | 200 | 1.7330 | 0.66 | 0.6290 | |
| | 1.4091 | 3.0 | 300 | 1.3255 | 0.78 | 0.7732 | |
| | 1.1217 | 4.0 | 400 | 1.1425 | 0.82 | 0.8186 | |
| | 1.0118 | 5.0 | 500 | 0.9657 | 0.85 | 0.8524 | |
| | 0.7186 | 6.0 | 600 | 0.7777 | 0.86 | 0.8609 | |
| | 0.4308 | 7.0 | 700 | 0.5975 | 0.905 | 0.9040 | |
| | 0.451 | 8.0 | 800 | 0.5240 | 0.915 | 0.9147 | |
| | 0.3558 | 9.0 | 900 | 0.5822 | 0.885 | 0.8853 | |
| | 0.2556 | 10.0 | 1000 | 0.5207 | 0.905 | 0.9052 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.3 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
