---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert
  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. -->

# bert

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: 0.1679
- Accuracy: 0.9669
- F1: 0.9667
- Precision: 0.9685
- Recall: 0.9669

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1054        | 1.0   | 38   | 1.0886          | 0.4106   | 0.2390 | 0.1686    | 0.4106 |
| 1.0709        | 2.0   | 76   | 0.9872          | 0.6490   | 0.5588 | 0.5174    | 0.6490 |
| 0.838         | 3.0   | 114  | 0.7455          | 0.6424   | 0.5447 | 0.4737    | 0.6424 |
| 0.2981        | 4.0   | 152  | 0.2033          | 0.9338   | 0.9340 | 0.9413    | 0.9338 |
| 0.1249        | 5.0   | 190  | 0.1285          | 0.9669   | 0.9668 | 0.9672    | 0.9669 |
| 0.1224        | 6.0   | 228  | 0.2481          | 0.9470   | 0.9476 | 0.9546    | 0.9470 |
| 0.0015        | 7.0   | 266  | 0.3061          | 0.9536   | 0.9535 | 0.9582    | 0.9536 |
| 0.0332        | 8.0   | 304  | 0.3735          | 0.9404   | 0.9406 | 0.9498    | 0.9404 |
| 0.1496        | 9.0   | 342  | 0.2024          | 0.9669   | 0.9670 | 0.9700    | 0.9669 |
| 0.0629        | 10.0  | 380  | 0.1679          | 0.9669   | 0.9667 | 0.9685    | 0.9669 |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.4.1
- Tokenizers 0.21.0