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sercetexam9/cs221-deberta-v3-base-finetuned

sourceHugging Facemitupdated 2y agoView on Hugging Face
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cs221-deberta-v3-base-finetuned

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

  • Loss: 0.3618
  • F1: 0.7829
  • Roc Auc: 0.8382
  • Accuracy: 0.5054

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: 2e-05
  • trainbatchsize: 32
  • evalbatchsize: 32
  • seed: 42
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: cosine
  • lrschedulerwarmup_steps: 100
  • num_epochs: 9

Training results

Training LossEpochStepValidation LossF1Roc AucAccuracy
0.581.0700.58150.42880.60880.1300
0.44462.01400.43560.66210.74960.3556
0.35453.02100.39410.71600.78930.4007
0.264.02800.37020.73870.80560.4368
0.24255.03500.36220.76410.82310.4783
0.19716.04200.35650.76890.82700.4892
0.15827.04900.36570.77030.82680.4892
0.1618.05600.36180.78290.83820.5054
0.149.06300.36130.77890.83450.5

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.21.0