| --- |
| license: apache-2.0 |
| base_model: ntu-spml/distilhubert |
| tags: |
| - generated_from_trainer |
| datasets: |
| - marsyas/gtzan |
| metrics: |
| - accuracy |
| model-index: |
| - name: AudioCourseU4-MusicClassification |
| 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: 0.88 |
| --- |
| |
| <!-- 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. --> |
|
|
| # AudioCourseU4-MusicClassification |
|
|
| 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: 0.8804 |
| - Accuracy: 0.88 |
|
|
| ## 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: 8e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - 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: 15 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.7993 | 1.0 | 225 | 1.5770 | 0.4 | |
| | 1.0767 | 2.0 | 450 | 0.9900 | 0.7 | |
| | 0.8292 | 3.0 | 675 | 0.8554 | 0.73 | |
| | 0.5892 | 4.0 | 900 | 0.8991 | 0.74 | |
| | 0.1584 | 5.0 | 1125 | 0.8473 | 0.78 | |
| | 0.0082 | 6.0 | 1350 | 0.9282 | 0.8 | |
| | 0.0094 | 7.0 | 1575 | 1.0036 | 0.82 | |
| | 0.0581 | 8.0 | 1800 | 1.2186 | 0.82 | |
| | 0.0021 | 9.0 | 2025 | 1.0192 | 0.83 | |
| | 0.0011 | 10.0 | 2250 | 0.8804 | 0.88 | |
| | 0.002 | 11.0 | 2475 | 1.1519 | 0.83 | |
| | 0.0009 | 12.0 | 2700 | 0.9439 | 0.87 | |
| | 0.0006 | 13.0 | 2925 | 1.1227 | 0.84 | |
| | 0.0008 | 14.0 | 3150 | 1.0344 | 0.86 | |
| | 0.0006 | 15.0 | 3375 | 1.0209 | 0.86 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.32.1 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
| |
