hubert-base-ls960-fsc

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

  • Loss: 0.0230
  • Accuracy: 0.9939

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: 0.0005
  • train_batch_size: 48
  • eval_batch_size: 48
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 192
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.9959 120 0.0706 0.9873
No log 2.0 241 0.0607 0.9868
No log 2.9959 361 0.0661 0.9831
No log 4.0 482 0.0518 0.9839
No log 4.9959 602 0.0230 0.9939
No log 6.0 723 0.0516 0.9858
No log 6.9959 843 0.0292 0.9937
No log 8.0 964 0.0276 0.9929
0.2849 8.9959 1084 0.0301 0.9937
0.2849 10.0 1205 0.0279 0.9937

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1
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