README.md

metadata

library_name: transformers
license: apache-2.0
base_model: sveyek/distilhubert-finetuned-gtzan-se-finetuned-gtzan-se-2
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: distilhubert-finetuned-gtzan-se-finetuned-gtzan-se-2-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: 0.82

distilhubert-finetuned-gtzan-se-finetuned-gtzan-se-2-finetuned-gtzan

This model is a fine-tuned version of sveyek/distilhubert-finetuned-gtzan-se-finetuned-gtzan-se-2 on the GTZAN dataset. It achieves the following results on the evaluation set:

• Loss: 0.8723
• Accuracy: 0.82

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-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0753	0.9956	56	0.8132	0.85
0.0024	1.9911	112	0.8723	0.82

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3