metadata

license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: hubert-base-ls960-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: 0.83

hubert-base-ls960-finetuned-gtzan

This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:

Loss: 1.0283
Accuracy: 0.83

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

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
2.2494	1.0	113	0.36	2.1568
1.7795	2.0	226	0.38	1.7904
1.5798	3.0	339	0.5	1.6144
1.6354	4.0	452	0.66	1.2584
0.9675	5.0	565	0.64	1.1453
0.995	6.0	678	0.67	0.9740
1.2052	7.0	791	0.68	1.0552
0.7028	8.0	904	0.74	0.8980
0.7472	9.0	1017	0.72	0.9431
0.3181	10.0	1130	0.75	0.8750
0.3948	11.0	1243	0.73	1.0047
0.3507	12.0	1356	0.81	0.8054
0.1785	13.0	1469	0.84	0.7866
0.2453	14.0	1582	0.82	0.8960
0.2832	15.0	1695	0.81	1.0770
0.2132	16.0	1808	0.82	0.9359
0.1398	17.0	1921	0.81	1.0800
0.292	18.0	2034	0.84	0.9867
0.0181	19.0	2147	0.82	1.0585
0.0399	20.0	2260	1.0283	0.83

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1