metadata
license: apache-2.0
base_model: yuval6967/wav2vec2-base-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-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: 0.82
pipeline_tag: audio-classification
wav2vec2-base-finetuned-gtzan-finetuned-gtzan
This model is a fine-tuned version of yuval6967/wav2vec2-base-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.8942
- Accuracy: 0.82
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
- gradient_accumulation_steps: 2
- 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 |
|---|---|---|---|---|
| 0.4822 | 0.9912 | 56 | 1.2225 | 0.78 |
| 0.3026 | 2.0 | 113 | 0.7599 | 0.85 |
| 0.2191 | 2.9912 | 169 | 0.8816 | 0.8 |
| 0.0791 | 4.0 | 226 | 1.1267 | 0.78 |
| 0.092 | 4.9912 | 282 | 0.8942 | 0.82 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1