Sandiago21's picture
update model card README.md
1d15b75
|
raw
history blame
2.57 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - marsyas/gtzan
metrics:
  - accuracy
model-index:
  - name: hubert-large-ls960-ft-finetuned-gtzan
    results: []

hubert-large-ls960-ft-finetuned-gtzan

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

  • Loss: 0.7096
  • Accuracy: 0.85

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: 8e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 18

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.2623 1.0 56 2.2399 0.21
1.881 1.99 112 1.7105 0.41
1.5793 2.99 168 1.6203 0.46
1.3018 4.0 225 1.3824 0.52
1.0219 5.0 281 0.9899 0.66
0.9047 5.99 337 0.8812 0.74
0.8353 6.99 393 0.7629 0.78
0.659 8.0 450 0.9674 0.71
0.645 9.0 506 0.8953 0.74
0.6233 9.99 562 0.6638 0.8
0.4155 10.99 618 0.6323 0.81
0.2689 12.0 675 0.5423 0.83
0.3714 13.0 731 0.6770 0.83
0.0692 13.99 787 0.6260 0.83
0.0778 14.99 843 0.5801 0.85
0.187 16.0 900 0.6722 0.83
0.1469 17.0 956 0.7473 0.85
0.1052 17.92 1008 0.7096 0.85

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3