bert-qa-lora / README.md
bhatia1289's picture
Model save
abf213d verified
metadata
library_name: peft
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_trainer
model-index:
  - name: bert-qa-lora
    results: []

bert-qa-lora

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

  • Loss: 1.2619

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: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.5073 1.0 36 3.4988
2.1278 2.0 72 1.5886
1.4468 3.0 108 1.2619

Framework versions

  • PEFT 0.14.0
  • Transformers 4.49.0
  • Pytorch 2.6.0+cu126
  • Datasets 3.3.1
  • Tokenizers 0.21.0