---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: tmp
  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. -->

# tmp

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4127
- Precision: 0.3197
- Recall: 0.2438
- F1: 0.2766

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.8182        | 0.35  | 500  | 0.5251          | 0.0       | 0.0    | 0.0    |
| 0.6835        | 0.7   | 1000 | 0.4857          | 0.0       | 0.0    | 0.0    |
| 0.6643        | 1.04  | 1500 | 0.4691          | 0.0       | 0.0    | 0.0    |
| 0.6403        | 1.39  | 2000 | 0.4580          | 0.4531    | 0.0349 | 0.0647 |
| 0.5617        | 1.74  | 2500 | 0.4528          | 0.3373    | 0.0673 | 0.1122 |
| 0.4896        | 2.09  | 3000 | 0.4265          | 0.3268    | 0.1611 | 0.2158 |
| 0.4451        | 2.43  | 3500 | 0.4087          | 0.3860    | 0.1791 | 0.2447 |
| 0.416         | 2.78  | 4000 | 0.4222          | 0.2937    | 0.2224 | 0.2531 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2