| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: facebook/hubert-base-ls960 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - marsyas/gtzan |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: hubert-base-ls960-finetuned-gtzan |
| | results: |
| | - task: |
| | name: Audio Classification |
| | type: audio-classification |
| | dataset: |
| | name: GTZAN |
| | type: marsyas/gtzan |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.7391304347826086 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # hubert-base-ls960-finetuned-gtzan |
| |
|
| | This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1234 |
| | - Accuracy: 0.7391 |
| |
|
| | ## 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: 15 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 1.4277 | 1.0 | 25 | 1.5627 | 0.4783 | |
| | | 1.4946 | 2.0 | 50 | 1.4727 | 0.5217 | |
| | | 1.051 | 3.0 | 75 | 1.3207 | 0.6087 | |
| | | 1.0897 | 4.0 | 100 | 1.3614 | 0.6522 | |
| | | 1.1461 | 5.0 | 125 | 1.3143 | 0.5652 | |
| | | 0.6919 | 6.0 | 150 | 1.1131 | 0.6087 | |
| | | 0.7273 | 7.0 | 175 | 1.4138 | 0.6522 | |
| | | 0.5955 | 8.0 | 200 | 1.2106 | 0.6957 | |
| | | 0.4823 | 9.0 | 225 | 1.1681 | 0.6087 | |
| | | 0.5178 | 10.0 | 250 | 1.1616 | 0.6522 | |
| | | 0.4635 | 11.0 | 275 | 0.9685 | 0.7826 | |
| | | 0.4622 | 12.0 | 300 | 0.9625 | 0.7826 | |
| | | 0.3048 | 13.0 | 325 | 1.0364 | 0.7391 | |
| | | 0.1576 | 14.0 | 350 | 1.0571 | 0.7391 | |
| | | 0.1876 | 15.0 | 375 | 1.1234 | 0.7391 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.51.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.5.1 |
| | - Tokenizers 0.21.1 |
| | |
