metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-bs-16
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.88
wav2vec2-base-finetuned-gtzan-bs-16
This model is a fine-tuned version of facebook/wav2vec2-base on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.5497
- 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: 16
- eval_batch_size: 16
- 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0557 | 1.0 | 57 | 1.9783 | 0.34 |
| 1.6173 | 2.0 | 114 | 1.6407 | 0.55 |
| 1.3884 | 3.0 | 171 | 1.2228 | 0.65 |
| 1.1082 | 4.0 | 228 | 1.0989 | 0.7 |
| 0.9112 | 5.0 | 285 | 0.8724 | 0.8 |
| 0.7985 | 6.0 | 342 | 0.8715 | 0.76 |
| 0.5456 | 7.0 | 399 | 0.6832 | 0.82 |
| 0.4842 | 8.0 | 456 | 0.6566 | 0.85 |
| 0.3419 | 9.0 | 513 | 0.6485 | 0.84 |
| 0.5821 | 10.0 | 570 | 0.5636 | 0.85 |
| 0.2112 | 11.0 | 627 | 0.4572 | 0.89 |
| 0.2005 | 12.0 | 684 | 0.5405 | 0.87 |
| 0.1314 | 13.0 | 741 | 0.4695 | 0.9 |
| 0.0866 | 14.0 | 798 | 0.5545 | 0.88 |
| 0.0594 | 15.0 | 855 | 0.5497 | 0.88 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3