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: 0.88
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:
- Loss: 0.5472
- 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: 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9984 | 1.0 | 113 | 1.9505 | 0.46 |
| 1.4188 | 2.0 | 226 | 1.5582 | 0.52 |
| 1.2867 | 3.0 | 339 | 1.1267 | 0.65 |
| 0.7716 | 4.0 | 452 | 0.9512 | 0.64 |
| 0.5553 | 5.0 | 565 | 0.9790 | 0.72 |
| 0.7491 | 6.0 | 678 | 0.7419 | 0.78 |
| 0.4399 | 7.0 | 791 | 0.5709 | 0.86 |
| 0.2489 | 8.0 | 904 | 0.6352 | 0.8 |
| 0.388 | 9.0 | 1017 | 0.5130 | 0.89 |
| 0.2066 | 10.0 | 1130 | 0.7185 | 0.86 |
| 0.1905 | 11.0 | 1243 | 0.5545 | 0.9 |
| 0.1312 | 12.0 | 1356 | 0.8126 | 0.85 |
| 0.0185 | 13.0 | 1469 | 0.4841 | 0.91 |
| 0.0154 | 14.0 | 1582 | 0.7167 | 0.86 |
| 0.0156 | 15.0 | 1695 | 0.5472 | 0.88 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1