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
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: 0.87
wav2vec2-base-finetuned-gtzan
This model is a fine-tuned version of facebook/wav2vec2-base on the GTZAN dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.87
- Loss: 0.4960
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
- 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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 1.9026 | 1.0 | 113 | 0.47 | 1.8157 |
| 1.4077 | 2.0 | 226 | 0.65 | 1.3151 |
| 1.1509 | 3.0 | 339 | 0.71 | 1.0788 |
| 0.8387 | 4.0 | 452 | 0.76 | 0.9460 |
| 0.5495 | 5.0 | 565 | 0.72 | 0.8380 |
| 0.5633 | 6.0 | 678 | 0.85 | 0.5783 |
| 0.4959 | 7.0 | 791 | 0.84 | 0.5539 |
| 0.1397 | 8.0 | 904 | 0.86 | 0.4837 |
| 0.1556 | 9.0 | 1017 | 0.87 | 0.5125 |
| 0.0785 | 10.0 | 1130 | 0.87 | 0.4960 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1