metadata

license: apache-2.0
base_model: NemesisAlm/distilhubert-finetuned-gtzan
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: GTZAN
          type: marsyas/gtzan
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.88

distilhubert-finetuned-gtzan

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

Loss: 1.1532
Accuracy: 0.88

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: 1e-100
train_batch_size: 12
eval_batch_size: 12
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 1e-19
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0011	0.27	20	1.1532	0.88
0.0081	0.53	40	1.1532	0.88
0.0005	0.8	60	1.1532	0.88

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.0+cu117
Datasets 2.13.1
Tokenizers 0.13.3