metadata
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
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: 0.9
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: 0.4199
- Accuracy: 0.9
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0281 | 1.0 | 113 | 0.7772 | 0.82 |
| 0.4417 | 2.0 | 226 | 0.6565 | 0.79 |
| 0.3046 | 3.0 | 339 | 0.5469 | 0.87 |
| 0.0048 | 4.0 | 452 | 0.4403 | 0.89 |
| 0.0019 | 5.0 | 565 | 0.5601 | 0.87 |
| 0.0007 | 6.0 | 678 | 0.5187 | 0.85 |
| 0.1911 | 7.0 | 791 | 0.4494 | 0.89 |
| 0.0001 | 8.0 | 904 | 0.4381 | 0.91 |
| 0.1045 | 9.0 | 1017 | 0.4187 | 0.9 |
| 0.0002 | 10.0 | 1130 | 0.4199 | 0.9 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0