metadata
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: xlm-roberta-base
metrics:
- accuracy
- f1
model-index:
- name: loha_fine_tuned_rte_XLMroberta
results: []
loha_fine_tuned_rte_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: 3.0980
- Accuracy: 0.6207
- F1: 0.6090
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: 0.003
- 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 |
|---|---|---|---|---|---|
| 0.8165 | 1.7241 | 50 | 0.7174 | 0.4828 | 0.3781 |
| 0.7386 | 3.4483 | 100 | 0.6616 | 0.6897 | 0.6523 |
| 0.7293 | 5.1724 | 150 | 0.7683 | 0.5172 | 0.4660 |
| 0.6773 | 6.8966 | 200 | 1.1129 | 0.4483 | 0.4324 |
| 0.4623 | 8.6207 | 250 | 1.7863 | 0.5862 | 0.5892 |
| 0.2532 | 10.3448 | 300 | 2.8440 | 0.5862 | 0.5483 |
| 0.0813 | 12.0690 | 350 | 3.0842 | 0.5517 | 0.5484 |
| 0.0478 | 13.7931 | 400 | 3.0980 | 0.6207 | 0.6090 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1