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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: 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. -->
# 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: 1.4763
- Accuracy: 0.6207
- F1: 0.5951
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7117 | 1.7241 | 50 | 0.7129 | 0.4138 | 0.2422 |
| 0.7033 | 3.4483 | 100 | 0.6997 | 0.4138 | 0.2422 |
| 0.6845 | 5.1724 | 150 | 0.6933 | 0.4828 | 0.4828 |
| 0.6378 | 6.8966 | 200 | 0.8005 | 0.4828 | 0.4668 |
| 0.4579 | 8.6207 | 250 | 0.9656 | 0.6207 | 0.5951 |
| 0.2521 | 10.3448 | 300 | 1.2302 | 0.6552 | 0.6018 |
| 0.1196 | 12.0690 | 350 | 1.4679 | 0.5862 | 0.5789 |
| 0.0653 | 13.7931 | 400 | 1.4763 | 0.6207 | 0.5951 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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