fine-tuned-gtzan – AI Model by ccourc23 | AlphaNeural AI

You can deploy this model and start earning money today!

ccourc23/
fine-tuned-gtzan

like

0

audio-classification

generated_from_trainer

ntu-spml/distilhubert

endpoints_compatible

Views

No views yet

fine-tuned-gtzan

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: 0.5559
Accuracy: 0.89
Acc: 0.89
F1: 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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.946	1.0	112	1.7832	0.52
1.3084	2.0	225	1.2228	0.65
0.8713	3.0	337	0.8974	0.75
0.6942	4.0	450	0.9075	0.77
0.4072	5.0	562	0.7447	0.78
0.2349	6.0	675	0.6456	0.81
0.197	7.0	787	0.6228	0.8
0.2246	8.0	900	0.5927	0.84
0.1987	9.0	1012	0.5558	0.88
0.1152	9.96	1120	0.5559	0.89

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2