distilhubert-finetuned-gtzan-v2

Maldopast/distilhubert-finetuned-gtzan-v2

distilhubert-finetuned-gtzan-v2 is a audio classification model from Maldopast. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

5% of all-time downloads

All-time downloads

Public

Repo size

190 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin94.8 MB · 100%

At a glance

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: hubert
Access: Public
Created: Jul 29, 2023
Updated: Jul 29, 2023
SHA: 8f2b09fe

Datasets

marsyas/gtzan

Model card

From the Hugging Face model README

distilhubert-finetuned-gtzan-v2

This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:

Loss: 0.4006
Accuracy: 0.89

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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4786	1.0	225	1.3772	0.67
1.0539	2.0	450	0.8660	0.78
0.8426	3.0	675	0.7087	0.79
0.5203	4.0	900	0.6213	0.8
0.2969	5.0	1125	0.5474	0.8
0.2166	6.0	1350	0.5594	0.86
0.0563	7.0	1575	0.3808	0.91
0.1048	8.0	1800	0.4006	0.89

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu117
Datasets 2.14.0
Tokenizers 0.13.3

Task: Audio Classification
Library: transformers
Type: hubert
License: apache-2.0
Created: Jul 29, 2023
Updated: Jul 29, 2023