test_trainer / README.md
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MaggieZhang/lora_bert_classification
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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: bert-base-cased
model-index:
  - name: test_trainer
    results: []

test_trainer

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3803
  • Accuracy: 0.842

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 125 0.6786 0.608
No log 2.0 250 0.6718 0.598
No log 3.0 375 0.6695 0.574
0.6888 4.0 500 0.6583 0.599
0.6888 5.0 625 0.6262 0.684
0.6888 6.0 750 0.5936 0.697
0.6888 7.0 875 0.5520 0.721
0.6057 8.0 1000 0.5149 0.746
0.6057 9.0 1125 0.4848 0.762
0.6057 10.0 1250 0.4558 0.779
0.6057 11.0 1375 0.4346 0.793
0.4583 12.0 1500 0.4215 0.801
0.4583 13.0 1625 0.4094 0.815
0.4583 14.0 1750 0.4027 0.816
0.4583 15.0 1875 0.3962 0.82
0.3847 16.0 2000 0.3926 0.823
0.3847 17.0 2125 0.3873 0.835
0.3847 18.0 2250 0.3857 0.833
0.3847 19.0 2375 0.3823 0.836
0.3565 20.0 2500 0.3819 0.837
0.3565 21.0 2625 0.3850 0.837
0.3565 22.0 2750 0.3806 0.839
0.3565 23.0 2875 0.3801 0.84
0.3348 24.0 3000 0.3808 0.842
0.3348 25.0 3125 0.3803 0.842

Framework versions

  • PEFT 0.8.2
  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.1