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scenario-TCR_data-cl-cardiff_cl_only

Text Classification
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PyTorch
deberta-v2
Generated from Trainer
Inference Endpoints
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scenario-TCR_data-cl-cardiff_cl_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-cl-cardiff_cl_only
    results: []

scenario-TCR_data-cl-cardiff_cl_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: 4.9878
  • Accuracy: 0.5278
  • F1: 0.5292

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 1.09 250 1.1991 0.5154 0.5166
0.731 2.17 500 1.5346 0.5316 0.5279
0.731 3.26 750 1.6658 0.5255 0.5251
0.3491 4.35 1000 1.9635 0.5185 0.5189
0.3491 5.43 1250 2.1732 0.5231 0.5221
0.1838 6.52 1500 3.0035 0.5239 0.5256
0.1838 7.61 1750 2.9315 0.5239 0.5258
0.122 8.7 2000 2.8799 0.5039 0.5009
0.122 9.78 2250 3.0551 0.5023 0.5037
0.0746 10.87 2500 3.2668 0.5262 0.5279
0.0746 11.96 2750 3.3828 0.5046 0.5062
0.0434 13.04 3000 3.8937 0.4954 0.4929
0.0434 14.13 3250 3.7629 0.5224 0.5235
0.0369 15.22 3500 4.1508 0.4931 0.4880
0.0369 16.3 3750 4.2268 0.5239 0.5240
0.0186 17.39 4000 4.3692 0.5054 0.5057
0.0186 18.48 4250 4.3635 0.5108 0.5108
0.0156 19.57 4500 4.4833 0.5062 0.5039
0.0156 20.65 4750 4.5300 0.5039 0.5043
0.0093 21.74 5000 4.5612 0.5239 0.5236
0.0093 22.83 5250 4.7381 0.5208 0.5216
0.0088 23.91 5500 4.6106 0.5324 0.5334
0.0088 25.0 5750 4.8040 0.5255 0.5269
0.0039 26.09 6000 4.8616 0.5262 0.5283
0.0039 27.17 6250 4.9228 0.5231 0.5247
0.0052 28.26 6500 5.1665 0.5008 0.5012
0.0052 29.35 6750 4.9878 0.5278 0.5292

Framework versions

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