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metadata
license: mit
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-KD-SCR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55
    results: []

scenario-KD-SCR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only55

This model is a fine-tuned version of haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only on the None dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Accuracy: 0.3333
  • F1: 0.1667

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: 32
  • eval_batch_size: 32
  • seed: 55
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.72 100 nan 0.3333 0.1667
No log 3.45 200 nan 0.3333 0.1667
No log 5.17 300 nan 0.3333 0.1667
No log 6.9 400 nan 0.3333 0.1667
1.106 8.62 500 nan 0.3333 0.1667
1.106 10.34 600 nan 0.3333 0.1667
1.106 12.07 700 nan 0.3333 0.1667
1.106 13.79 800 nan 0.3333 0.1667
1.106 15.52 900 nan 0.3333 0.1667
0.0 17.24 1000 nan 0.3333 0.1667
0.0 18.97 1100 nan 0.3333 0.1667
0.0 20.69 1200 nan 0.3333 0.1667
0.0 22.41 1300 nan 0.3333 0.1667
0.0 24.14 1400 nan 0.3333 0.1667
0.0 25.86 1500 nan 0.3333 0.1667
0.0 27.59 1600 nan 0.3333 0.1667
0.0 29.31 1700 nan 0.3333 0.1667

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3