metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
results: []
distilhubert-finetuned-gtzan
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.8818
- Accuracy: 0.85
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: 17
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5851 | 1.0 | 113 | 1.7243 | 0.5 |
| 1.2937 | 2.0 | 226 | 1.2310 | 0.68 |
| 0.9718 | 3.0 | 339 | 0.8918 | 0.76 |
| 0.6613 | 4.0 | 452 | 0.6837 | 0.81 |
| 0.3693 | 5.0 | 565 | 0.6250 | 0.82 |
| 0.2991 | 6.0 | 678 | 0.5740 | 0.82 |
| 0.1381 | 7.0 | 791 | 0.5874 | 0.83 |
| 0.2047 | 8.0 | 904 | 0.5824 | 0.86 |
| 0.1192 | 9.0 | 1017 | 0.7106 | 0.83 |
| 0.0652 | 10.0 | 1130 | 0.6576 | 0.87 |
| 0.0105 | 11.0 | 1243 | 0.8236 | 0.84 |
| 0.0074 | 12.0 | 1356 | 0.7874 | 0.85 |
| 0.0064 | 13.0 | 1469 | 0.9066 | 0.84 |
| 0.0041 | 14.0 | 1582 | 0.8426 | 0.85 |
| 0.0038 | 15.0 | 1695 | 0.8676 | 0.84 |
| 0.0039 | 16.0 | 1808 | 0.8820 | 0.85 |
| 0.0036 | 17.0 | 1921 | 0.8818 | 0.85 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3