metadata
base_model: m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan
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: 0.98
wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan
This model is a fine-tuned version of m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6843
- Accuracy: 0.98
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
- gradient_accumulation_steps: 8
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1932 | 0.9976 | 53 | 2.1037 | 0.82 |
| 1.9212 | 1.9953 | 106 | 1.8040 | 0.8267 |
| 1.6379 | 2.9929 | 159 | 1.5650 | 0.8667 |
| 1.4604 | 3.9906 | 212 | 1.3201 | 0.9267 |
| 1.2249 | 4.9882 | 265 | 1.1253 | 0.94 |
| 1.075 | 5.9859 | 318 | 0.9814 | 0.96 |
| 0.911 | 6.9835 | 371 | 0.8447 | 0.9667 |
| 0.852 | 8.0 | 425 | 0.7628 | 0.9667 |
| 0.7625 | 8.9976 | 478 | 0.7117 | 0.9733 |
| 0.7099 | 9.9765 | 530 | 0.6843 | 0.98 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1