ASAP_FineTuningBERT_AugV8_k1_task1_organization_fold0

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0211
  • Qwk: 0.0700
  • Mse: 2.0211
  • Rmse: 1.4217

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: 16
  • eval_batch_size: 16
  • seed: 42
  • 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
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Qwk Mse Rmse
No log 1.0 5 5.6489 0.0122 5.6489 2.3767
6.0082 2.0 10 2.7603 0.0 2.7603 1.6614
6.0082 3.0 15 2.0211 0.0700 2.0211 1.4217

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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