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