| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: ntu-spml/distilhubert |
| tags: |
| - generated_from_trainer |
| datasets: |
| - calixtemayoraz/FMA-music-dataset |
| metrics: |
| - accuracy |
| model-index: |
| - name: distilhubert-finetuned-FMA-music |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: FMA-music-dataset |
| type: calixtemayoraz/FMA-music-dataset |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.45754716981132076 |
| --- |
| |
| <!-- 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. --> |
|
|
| # distilhubert-finetuned-FMA-music |
|
|
| This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the FMA-music-dataset dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.8929 |
| - Accuracy: 0.4575 |
|
|
| ## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.0384 | 1.0 | 238 | 2.2583 | 0.2358 | |
| | 1.9204 | 2.0 | 476 | 2.1387 | 0.2972 | |
| | 1.6768 | 3.0 | 714 | 1.9356 | 0.3774 | |
| | 1.7940 | 4.0 | 952 | 1.8584 | 0.3868 | |
| | 1.5281 | 5.0 | 1190 | 1.7814 | 0.4434 | |
| | 1.1608 | 6.0 | 1428 | 1.8745 | 0.4151 | |
| | 1.2103 | 7.0 | 1666 | 1.8066 | 0.4434 | |
| | 0.8522 | 8.0 | 1904 | 1.8688 | 0.4434 | |
| | 0.7455 | 9.0 | 2142 | 1.8818 | 0.4528 | |
| | 0.5444 | 10.0 | 2380 | 1.8929 | 0.4575 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
|
|
