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scenario-TCR_data-en-cardiff_eng_only

Text Classification
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PyTorch
deberta-v2
Generated from Trainer
Inference Endpoints
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scenario-TCR_data-en-cardiff_eng_only / README.md
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metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: scenario-TCR_data-en-cardiff_eng_only
    results: []

scenario-TCR_data-en-cardiff_eng_only

This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.5981
  • Accuracy: 0.5798
  • F1: 0.5830

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: 66
  • 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 1.03 60 1.0880 0.5295 0.5251
No log 2.07 120 1.0869 0.5617 0.5392
No log 3.1 180 1.1333 0.5789 0.5818
No log 4.14 240 1.2897 0.5728 0.5743
No log 5.17 300 1.4495 0.5899 0.5944
No log 6.21 360 1.9107 0.5573 0.5582
No log 7.24 420 1.8983 0.5851 0.5883
No log 8.28 480 2.1481 0.5816 0.5838
0.4492 9.31 540 2.1906 0.5697 0.5681
0.4492 10.34 600 2.4558 0.5692 0.5658
0.4492 11.38 660 2.2698 0.5891 0.5917
0.4492 12.41 720 2.6192 0.5816 0.5832
0.4492 13.45 780 2.8040 0.5825 0.5866
0.4492 14.48 840 3.0573 0.5754 0.5790
0.4492 15.52 900 2.8448 0.5847 0.5872
0.4492 16.55 960 3.2238 0.5829 0.5874
0.0555 17.59 1020 3.2796 0.5811 0.5852
0.0555 18.62 1080 3.2371 0.5869 0.5878
0.0555 19.66 1140 3.4683 0.5802 0.5831
0.0555 20.69 1200 3.4679 0.5772 0.5793
0.0555 21.72 1260 3.4337 0.5877 0.5912
0.0555 22.76 1320 3.5059 0.5763 0.5792
0.0555 23.79 1380 3.6144 0.5807 0.5851
0.0555 24.83 1440 3.5076 0.5847 0.5874
0.0086 25.86 1500 3.5835 0.5842 0.5878
0.0086 26.9 1560 3.5517 0.5847 0.5872
0.0086 27.93 1620 3.6182 0.5825 0.5855
0.0086 28.97 1680 3.5885 0.5816 0.5847
0.0086 30.0 1740 3.5981 0.5798 0.5830

Framework versions

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