hubert-base-ls960-finetuned-ic-slurp-no-pretrain

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: 3.2153
  • Accuracy: 0.2587

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: 24
  • eval_batch_size: 24
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 96
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
3.9001 1.0 527 3.9015 0.0736
3.8219 2.0 1055 3.8454 0.0766
3.7453 3.0 1582 3.7615 0.0837
3.7202 4.0 2110 3.7143 0.0912
3.649 5.0 2637 3.6899 0.0868
3.6459 6.0 3165 3.6261 0.1077
3.5103 7.0 3692 3.5303 0.1216
3.4177 8.0 4220 3.4234 0.1503
3.3008 9.0 4747 3.3969 0.1586
3.0881 10.0 5275 3.2262 0.1993
2.9312 11.0 5802 3.1606 0.2214
2.7669 12.0 6330 3.1171 0.2364
2.5412 13.0 6857 3.1180 0.2495
2.4121 14.0 7385 3.1714 0.2458
2.1346 15.0 7912 3.2153 0.2587
2.0515 16.0 8440 3.3048 0.2564
1.7885 17.0 8967 3.3968 0.2558
1.6461 18.0 9495 3.5184 0.2511
1.4339 19.0 10022 3.7439 0.2549
1.2975 20.0 10550 3.8629 0.2549

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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