| --- |
| 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: all |
| split: train |
| args: all |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.83 |
| --- |
| |
| <!-- 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: 1.0283 |
| - Accuracy: 0.83 |
|
|
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Accuracy | Validation Loss | |
| |:-------------:|:-----:|:----:|:--------:|:---------------:| |
| | 2.2494 | 1.0 | 113 | 0.36 | 2.1568 | |
| | 1.7795 | 2.0 | 226 | 0.38 | 1.7904 | |
| | 1.5798 | 3.0 | 339 | 0.5 | 1.6144 | |
| | 1.6354 | 4.0 | 452 | 0.66 | 1.2584 | |
| | 0.9675 | 5.0 | 565 | 0.64 | 1.1453 | |
| | 0.995 | 6.0 | 678 | 0.67 | 0.9740 | |
| | 1.2052 | 7.0 | 791 | 0.68 | 1.0552 | |
| | 0.7028 | 8.0 | 904 | 0.74 | 0.8980 | |
| | 0.7472 | 9.0 | 1017 | 0.72 | 0.9431 | |
| | 0.3181 | 10.0 | 1130 | 0.75 | 0.8750 | |
| | 0.3948 | 11.0 | 1243 | 0.73 | 1.0047 | |
| | 0.3507 | 12.0 | 1356 | 0.81 | 0.8054 | |
| | 0.1785 | 13.0 | 1469 | 0.84 | 0.7866 | |
| | 0.2453 | 14.0 | 1582 | 0.82 | 0.8960 | |
| | 0.2832 | 15.0 | 1695 | 0.81 | 1.0770 | |
| | 0.2132 | 16.0 | 1808 | 0.82 | 0.9359 | |
| | 0.1398 | 17.0 | 1921 | 0.81 | 1.0800 | |
| | 0.292 | 18.0 | 2034 | 0.84 | 0.9867 | |
| | 0.0181 | 19.0 | 2147 | 0.82 | 1.0585 | |
| | 0.0399 | 20.0 | 2260 | 1.0283 | 0.83 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.34.1 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
| |
