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scenario-KD-PO-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: 39.4604
  • Accuracy: 0.4537
  • F1: 0.4426

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 24.2103 0.4616 0.4518
No log 3.45 200 29.3271 0.4255 0.3714
No log 5.17 300 29.8979 0.4489 0.4414
No log 6.9 400 31.7211 0.4669 0.4627
15.3839 8.62 500 37.0421 0.4581 0.4492
15.3839 10.34 600 32.5884 0.4669 0.4658
15.3839 12.07 700 39.9517 0.4493 0.4332
15.3839 13.79 800 38.5249 0.4630 0.4470
15.3839 15.52 900 38.7918 0.4414 0.4286
2.5437 17.24 1000 40.0345 0.4524 0.4391
2.5437 18.97 1100 38.3918 0.4612 0.4527
2.5437 20.69 1200 41.3974 0.4396 0.4169
2.5437 22.41 1300 38.7372 0.4603 0.4532
2.5437 24.14 1400 40.1541 0.4405 0.4288
1.0429 25.86 1500 40.0459 0.4568 0.4383
1.0429 27.59 1600 39.3779 0.4590 0.4457
1.0429 29.31 1700 39.4604 0.4537 0.4426

Framework versions

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