metadata
library_name: transformers
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:
- Loss: 0.5916
- Accuracy: 0.87
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 1.9043 | 1.0 | 113 | 0.46 | 1.8057 |
| 1.2603 | 2.0 | 226 | 0.58 | 1.3549 |
| 1.1442 | 3.0 | 339 | 0.68 | 1.0001 |
| 0.6053 | 4.0 | 452 | 0.68 | 0.9841 |
| 0.5621 | 5.0 | 565 | 0.69 | 0.9519 |
| 0.541 | 6.0 | 678 | 0.79 | 0.6576 |
| 0.3868 | 7.0 | 791 | 0.86 | 0.4867 |
| 0.1518 | 8.0 | 904 | 0.84 | 0.5443 |
| 0.1699 | 9.0 | 1017 | 0.91 | 0.4024 |
| 0.0798 | 10.0 | 1130 | 0.5878 | 0.86 |
| 0.1869 | 11.0 | 1243 | 0.6483 | 0.86 |
| 0.1439 | 12.0 | 1356 | 0.5916 | 0.87 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0