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capricious-gnu-139

Text Classification
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Safetensors
deberta-v2
Generated from Trainer
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metadata
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-xsmall
tags:
  - generated_from_trainer
model-index:
  - name: capricious-gnu-139
    results: []

capricious-gnu-139

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

  • Loss: 0.1831
  • Hamming Loss: 0.0661
  • Zero One Loss: 0.4537
  • Jaccard Score: 0.4105
  • Hamming Loss Optimised: 0.0659
  • Hamming Loss Threshold: 0.6135
  • Zero One Loss Optimised: 0.4087
  • Zero One Loss Threshold: 0.4316
  • Jaccard Score Optimised: 0.3479
  • Jaccard Score Threshold: 0.3462

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: 5.0943791435964314e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 2024
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 9

Training results

Training Loss Epoch Step Validation Loss Hamming Loss Zero One Loss Jaccard Score Hamming Loss Optimised Hamming Loss Threshold Zero One Loss Optimised Zero One Loss Threshold Jaccard Score Optimised Jaccard Score Threshold
0.4159 1.0 100 0.3376 0.1123 1.0 1.0 0.1123 0.9000 1.0 0.9000 1.0 0.9000
0.3121 2.0 200 0.2841 0.0932 0.8113 0.8087 0.0931 0.4416 0.6963 0.1641 0.6101 0.1642
0.2602 3.0 300 0.2338 0.092 0.785 0.7819 0.0765 0.3980 0.6113 0.3139 0.5072 0.2086
0.2174 4.0 400 0.2063 0.0712 0.5975 0.5703 0.0698 0.4494 0.5363 0.3378 0.4363 0.2553
0.1896 5.0 500 0.1967 0.0694 0.5813 0.5551 0.0661 0.4552 0.4513 0.3622 0.3900 0.2346
0.1726 6.0 600 0.1910 0.07 0.4988 0.4614 0.0695 0.5944 0.4400 0.4036 0.3569 0.3149
0.1618 7.0 700 0.1861 0.0679 0.475 0.4339 0.0651 0.5430 0.4237 0.4130 0.3652 0.3483
0.1522 8.0 800 0.1845 0.0683 0.4712 0.4328 0.0663 0.5807 0.4337 0.4266 0.3585 0.3310
0.1484 9.0 900 0.1831 0.0661 0.4537 0.4105 0.0659 0.6135 0.4087 0.4316 0.3479 0.3462

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.5.1+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.3