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: 0.5240
- 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6746 | 1.0 | 112 | 0.6682 | 0.79 |
| 0.4141 | 2.0 | 225 | 0.5245 | 0.85 |
| 0.2933 | 3.0 | 337 | 0.3968 | 0.87 |
| 0.0352 | 4.0 | 450 | 0.3729 | 0.9 |
| 0.0029 | 5.0 | 562 | 0.6066 | 0.88 |
| 0.0036 | 6.0 | 675 | 0.5297 | 0.89 |
| 0.0001 | 7.0 | 787 | 0.5816 | 0.89 |
| 0.0072 | 8.0 | 900 | 0.5307 | 0.9 |
| 0.0052 | 9.0 | 1012 | 0.5536 | 0.9 |
| 0.0001 | 10.0 | 1125 | 0.5478 | 0.9 |
| 0.0001 | 11.0 | 1237 | 0.5201 | 0.9 |
| 0.0001 | 12.0 | 1350 | 0.5263 | 0.9 |
| 0.0001 | 13.0 | 1462 | 0.5223 | 0.9 |
| 0.0 | 14.0 | 1575 | 0.5225 | 0.9 |
| 0.0001 | 14.93 | 1680 | 0.5240 | 0.9 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3