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lora_fine_tuned_boolq_XLMroberta
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metadata
license: mit
library_name: peft
tags:
  - generated_from_trainer
base_model: xlm-roberta-base
metrics:
  - accuracy
  - f1
model-index:
  - name: lora_fine_tuned_boolq_XLMroberta
    results: []

lora_fine_tuned_boolq_XLMroberta

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

  • Loss: 0.5832
  • Accuracy: 0.7778
  • F1: 0.6806

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
  • 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
  • training_steps: 400

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.699 4.1667 50 0.6271 0.7778 0.6806
0.6568 8.3333 100 0.5902 0.7778 0.6806
0.6613 12.5 150 0.5955 0.7778 0.6806
0.6531 16.6667 200 0.5899 0.7778 0.6806
0.6527 20.8333 250 0.5876 0.7778 0.6806
0.6534 25.0 300 0.5876 0.7778 0.6806
0.6568 29.1667 350 0.5843 0.7778 0.6806
0.6522 33.3333 400 0.5832 0.7778 0.6806

Framework versions

  • PEFT 0.11.1
  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1