metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-gtzan-efficient-label-smoothed
results: []
hubert-base-ls960-finetuned-gtzan-efficient-label-smoothed
This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 2.2778
- Accuracy: 0.84
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: 30
- label_smoothing_factor: 0.9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2946 | 1.0 | 113 | 2.2960 | 0.42 |
| 2.2821 | 2.0 | 226 | 2.2858 | 0.63 |
| 2.2842 | 3.0 | 339 | 2.2848 | 0.68 |
| 2.2685 | 4.0 | 452 | 2.2836 | 0.71 |
| 2.2688 | 5.0 | 565 | 2.2838 | 0.71 |
| 2.2901 | 6.0 | 678 | 2.2804 | 0.75 |
| 2.2683 | 7.0 | 791 | 2.2831 | 0.7 |
| 2.2695 | 8.0 | 904 | 2.2833 | 0.75 |
| 2.268 | 9.0 | 1017 | 2.2793 | 0.8 |
| 2.2836 | 10.0 | 1130 | 2.2867 | 0.68 |
| 2.2704 | 11.0 | 1243 | 2.2811 | 0.78 |
| 2.2665 | 12.0 | 1356 | 2.2783 | 0.83 |
| 2.2663 | 13.0 | 1469 | 2.2782 | 0.85 |
| 2.2669 | 14.0 | 1582 | 2.2759 | 0.88 |
| 2.266 | 15.0 | 1695 | 2.2800 | 0.82 |
| 2.266 | 16.0 | 1808 | 2.2797 | 0.82 |
| 2.266 | 17.0 | 1921 | 2.2778 | 0.84 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.1.0.dev20230627+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3