metadata

license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: wav2vec2-base-960h-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-960h-finetuned-gtzan

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the GTZAN dataset. It achieves the following results on the evaluation set:

Loss: 0.5055
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: 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: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.2648	1.0	57	2.2400	0.15
2.167	2.0	114	2.1032	0.17
1.8573	3.0	171	1.7658	0.32
1.5347	4.0	228	1.6620	0.45
1.6134	5.0	285	1.5017	0.49
1.2903	6.0	342	1.4639	0.49
1.29	7.0	399	1.1893	0.66
1.1094	8.0	456	1.1425	0.67
1.1023	9.0	513	1.0173	0.72
0.9244	10.0	570	0.9069	0.79
0.7764	11.0	627	0.9314	0.74
0.6899	12.0	684	0.7919	0.78
0.6033	13.0	741	0.7145	0.8
0.4834	14.0	798	0.8896	0.76
0.4409	15.0	855	0.7083	0.82
0.3653	16.0	912	0.5633	0.83
0.3986	17.0	969	0.5475	0.89
0.2725	18.0	1026	0.5044	0.87
0.3569	19.0	1083	0.5044	0.85
0.2089	20.0	1140	0.5055	0.87

Framework versions

Transformers 4.39.3
Pytorch 2.0.1+cu117
Datasets 2.18.0
Tokenizers 0.15.2