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---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_copa_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_copa_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: 0.6931
- Accuracy: 0.55
- F1: 0.3903
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7048 | 1.0 | 50 | 0.6931 | 0.55 | 0.3903 |
| 0.7085 | 2.0 | 100 | 0.6931 | 0.55 | 0.3903 |
| 0.7212 | 3.0 | 150 | 0.6931 | 0.55 | 0.3903 |
| 0.7161 | 4.0 | 200 | 0.6931 | 0.55 | 0.3903 |
| 0.7113 | 5.0 | 250 | 0.6931 | 0.55 | 0.3903 |
| 0.72 | 6.0 | 300 | 0.6931 | 0.55 | 0.3903 |
| 0.7292 | 7.0 | 350 | 0.6931 | 0.55 | 0.3903 |
| 0.6998 | 8.0 | 400 | 0.6931 | 0.55 | 0.3903 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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