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hubert-base-ls960-finetuned-common_language-finetuned-common_language

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

  • Loss: 1.4164
  • Accuracy: 0.8011

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
2.9713 1.0 2774 3.0764 0.1615
1.7443 2.0 5549 1.8279 0.4734
1.1304 3.0 8323 1.3202 0.6371
1.2718 4.0 11098 1.1571 0.6968
0.769 5.0 13872 1.2917 0.7127
0.2656 6.0 16647 1.1549 0.7479
0.2939 7.0 19421 1.2372 0.7736
0.1278 8.0 22196 1.2985 0.7875
0.5175 9.0 24970 1.3664 0.7986
0.0547 10.0 27740 1.4164 0.8011

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Dataset used to train AescF/hubert-base-ls960-finetuned-common_language

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Evaluation results