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-bs-16
    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: 0.88

wav2vec2-base-finetuned-gtzan-bs-16

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: 0.5497
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: 16
eval_batch_size: 16
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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0557	1.0	57	1.9783	0.34
1.6173	2.0	114	1.6407	0.55
1.3884	3.0	171	1.2228	0.65
1.1082	4.0	228	1.0989	0.7
0.9112	5.0	285	0.8724	0.8
0.7985	6.0	342	0.8715	0.76
0.5456	7.0	399	0.6832	0.82
0.4842	8.0	456	0.6566	0.85
0.3419	9.0	513	0.6485	0.84
0.5821	10.0	570	0.5636	0.85
0.2112	11.0	627	0.4572	0.89
0.2005	12.0	684	0.5405	0.87
0.1314	13.0	741	0.4695	0.9
0.0866	14.0	798	0.5545	0.88
0.0594	15.0	855	0.5497	0.88

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3