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rajevan123/STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe-test_augmentation

sourceHugging Facemitupdated 3y agoView on Hugging Face
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STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe-test_augmentation

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: 1.2431
  • —Accuracy: 0.4627

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: 3e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
No log1.03601.75000.2429
1.74742.07201.72550.2451
1.6813.010801.62910.3332
1.6814.014401.47640.4130
1.54195.018001.41650.4159
1.40146.021601.35480.4336
1.32697.025201.31220.4456
1.32698.028801.30030.4529
1.28219.032401.28300.4572
1.251610.036001.27570.4576
1.251611.039601.26190.4590
1.230412.043201.25010.4670
1.217213.046801.26740.4583
1.204314.050401.24590.4656
1.204315.054001.24640.4627
1.195616.057601.24390.4645
1.181417.061201.23950.4648
1.181418.064801.24290.4637
1.181619.068401.24500.4634
1.179420.072001.24310.4627

Framework versions

  • —PEFT 0.10.0
  • —Transformers 4.38.2
  • —Pytorch 2.2.1+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.15.2