metadata
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
results: []
ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.7408
- 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5687 | 1.0 | 450 | 1.3520 | 0.58 |
| 0.0014 | 2.0 | 900 | 0.9949 | 0.7 |
| 0.2778 | 3.0 | 1350 | 0.7536 | 0.84 |
| 0.0042 | 4.0 | 1800 | 0.9976 | 0.86 |
| 0.0001 | 5.0 | 2250 | 0.7859 | 0.85 |
| 0.0002 | 6.0 | 2700 | 0.9659 | 0.86 |
| 0.0 | 7.0 | 3150 | 0.8016 | 0.88 |
| 0.0 | 8.0 | 3600 | 0.5691 | 0.88 |
| 0.0 | 9.0 | 4050 | 0.7230 | 0.88 |
| 0.0 | 10.0 | 4500 | 0.7408 | 0.88 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3