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library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: trainer_output
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. -->
# trainer_output
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0023
- Accuracy: 0.8598
- F1: 0.8668
- Precision: 0.8770
- Recall: 0.8598
## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 0.2439 | 20 | 1.6724 | 0.8537 | 0.8597 | 0.8721 | 0.8537 |
| No log | 0.4878 | 40 | 2.1847 | 0.8598 | 0.8618 | 0.8640 | 0.8598 |
| 0.3126 | 0.7317 | 60 | 2.0168 | 0.8598 | 0.8630 | 0.8673 | 0.8598 |
| 0.3126 | 0.9756 | 80 | 2.4119 | 0.8780 | 0.8804 | 0.8904 | 0.8780 |
| 0.2521 | 1.2195 | 100 | 2.2020 | 0.8902 | 0.8884 | 0.8899 | 0.8902 |
| 0.2521 | 1.4634 | 120 | 2.2252 | 0.8902 | 0.8893 | 0.8908 | 0.8902 |
| 0.2521 | 1.7073 | 140 | 1.9534 | 0.8476 | 0.8579 | 0.8738 | 0.8476 |
| 0.2102 | 1.9512 | 160 | 2.0566 | 0.8963 | 0.8952 | 0.8948 | 0.8963 |
| 0.2102 | 2.1951 | 180 | 2.1647 | 0.8659 | 0.8714 | 0.8799 | 0.8659 |
| 0.0475 | 2.4390 | 200 | 2.2178 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
| 0.0475 | 2.6829 | 220 | 2.2616 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
| 0.0475 | 2.9268 | 240 | 2.2667 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
### Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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