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scenario-KD-SCR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66

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deberta-v2
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metadata
base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
library_name: transformers
license: mit
metrics:
  - accuracy
  - f1
tags:
  - generated_from_trainer
model-index:
  - name: scenario-KD-SCR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66
    results: []

scenario-KD-SCR-CDF-EN-FROM-CL-D2_data-en-cardiff_eng_only66

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: 533.1400
  • Accuracy: 0.3435
  • F1: 0.2746

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: 8
  • eval_batch_size: 32
  • seed: 66
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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 1.7391 100 630.5721 0.3347 0.2738
No log 3.4783 200 605.2021 0.3329 0.2631
No log 5.2174 300 588.4736 0.3289 0.1894
No log 6.9565 400 579.8921 0.3302 0.2716
573.1106 8.6957 500 571.2699 0.3510 0.2838
573.1106 10.4348 600 564.0858 0.3422 0.2638
573.1106 12.1739 700 560.2971 0.3364 0.2551
573.1106 13.9130 800 553.0224 0.3457 0.2748
573.1106 15.6522 900 549.0078 0.3426 0.2771
468.2501 17.3913 1000 545.7394 0.3435 0.2815
468.2501 19.1304 1100 541.9386 0.3496 0.2813
468.2501 20.8696 1200 539.8362 0.3519 0.2784
468.2501 22.6087 1300 537.6076 0.3567 0.2837
468.2501 24.3478 1400 535.7779 0.3519 0.2832
433.4717 26.0870 1500 533.8346 0.3580 0.2865
433.4717 27.8261 1600 533.4024 0.3430 0.2749
433.4717 29.5652 1700 533.1400 0.3435 0.2746

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.14.5
  • Tokenizers 0.19.1