---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# loha_fine_tuned_rte_XLMroberta

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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