| --- |
| license: apache-2.0 |
| base_model: ntu-spml/distilhubert |
| tags: |
| - generated_from_trainer |
| datasets: |
| - marsyas/gtzan |
| metrics: |
| - accuracy |
| model-index: |
| - name: ts-distilhubert-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. --> |
|
|
| # ts-distilhubert-finetuned-gtzan |
|
|
| This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6580 |
| - 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: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.9712 | 1.0 | 113 | 1.9122 | 0.47 | |
| | 1.2031 | 2.0 | 226 | 1.3221 | 0.61 | |
| | 0.9693 | 3.0 | 339 | 0.9988 | 0.72 | |
| | 0.871 | 4.0 | 452 | 0.8685 | 0.77 | |
| | 0.4698 | 5.0 | 565 | 0.7312 | 0.81 | |
| | 0.4306 | 6.0 | 678 | 0.7236 | 0.78 | |
| | 0.2482 | 7.0 | 791 | 0.8157 | 0.76 | |
| | 0.2672 | 8.0 | 904 | 0.5917 | 0.85 | |
| | 0.1592 | 9.0 | 1017 | 0.6369 | 0.83 | |
| | 0.1181 | 10.0 | 1130 | 0.6580 | 0.83 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.36.0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
| |
