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rajevan123/STS-Lora-Fine-Tuning-Capstone-bert-testing-21-with-lower-r

sourceHugging Facemitupdated 3y agoView on Hugging Face
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STS-Lora-Fine-Tuning-Capstone-bert-testing-21-with-lower-r

This model is a fine-tuned version of dslim/bert-base-NER on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.5146
  • —Accuracy: 0.3604

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 log1.01801.74930.2429
No log2.03601.74090.2444
1.70633.05401.73150.2408
1.70634.07201.71320.2741
1.70635.09001.67860.2879
1.66536.010801.66170.2959
1.66537.012601.63990.3031
1.66538.014401.61090.3205
1.59499.016201.59370.3292
1.594910.018001.57150.3321
1.594911.019801.56270.3387
1.534412.021601.55430.3459
1.534413.023401.53960.3590
1.493214.025201.52950.3524
1.493215.027001.52700.3568
1.493216.028801.52400.3575
1.473817.030601.51770.3604
1.473818.032401.51850.3590
1.473819.034201.51560.3604
1.460920.036001.51460.3604

Framework versions

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