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: 0.84

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: 1.0690
Accuracy: 0.84

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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0298	1.0	113	1.9942	0.42
1.6308	2.0	226	1.7948	0.45
1.4047	3.0	339	1.6728	0.4
1.0438	4.0	452	1.2557	0.63
1.0471	5.0	565	1.0976	0.66
0.8658	6.0	678	0.9722	0.64
0.7625	7.0	791	0.7211	0.79
0.6197	8.0	904	0.9618	0.71
0.2382	9.0	1017	0.5927	0.85
0.275	10.0	1130	0.9532	0.75
0.2681	11.0	1243	1.1366	0.76
0.2315	12.0	1356	1.1621	0.79
0.0142	13.0	1469	0.9571	0.84
0.0151	14.0	1582	0.9650	0.84
0.1348	15.0	1695	1.2902	0.8
0.0082	16.0	1808	1.0652	0.83
0.0054	17.0	1921	0.9985	0.83
0.0049	18.0	2034	1.0041	0.85
0.0052	19.0	2147	1.0800	0.85
0.0044	20.0	2260	1.0690	0.84

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2