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: 0.91
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: 0.2797
- Accuracy: 0.91
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: 4
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.7205 | 1.0 | 56 | 0.7984 | 0.77 |
| 0.3329 | 1.99 | 112 | 0.5558 | 0.83 |
| 0.1958 | 2.99 | 168 | 0.5639 | 0.81 |
| 0.0955 | 4.0 | 225 | 0.4130 | 0.85 |
| 0.0683 | 5.0 | 281 | 0.4681 | 0.87 |
| 0.0012 | 5.99 | 337 | 0.3278 | 0.89 |
| 0.0016 | 6.99 | 393 | 0.3064 | 0.92 |
| 0.0005 | 8.0 | 450 | 0.2827 | 0.91 |
| 0.0533 | 9.0 | 506 | 0.2788 | 0.91 |
| 0.0002 | 9.96 | 560 | 0.2797 | 0.91 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3