---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: XLM-R-BASE-Finetune-step2-finetune-and-eval-may31-volcanic-moon-1-D-05-31-T-03-38
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# XLM-R-BASE-Finetune-step2-finetune-and-eval-may31-volcanic-moon-1-D-05-31-T-03-38

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: 0.3977
- Precision 0: 0.8721
- Precision 1: 0.8029
- Recall 0: 0.8633
- Recall 1: 0.8148
- F1 0: 0.8677
- F1 1: 0.8088
- Precision Weighted: 0.8440
- Recall Weighted: 0.8436
- F1 Weighted: 0.8438
- F1 Macro: 0.8382

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision 0 | Precision 1 | Recall 0 | Recall 1 | F1 0   | F1 1   | Precision Weighted | Recall Weighted | F1 Weighted | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-----------:|:--------:|:--------:|:------:|:------:|:------------------:|:---------------:|:-----------:|:--------:|
| 0.5501        | 1.0   | 469  | 0.4524          | 0.7699      | 0.8995      | 0.9556   | 0.5823   | 0.8528 | 0.7069 | 0.8226             | 0.804           | 0.7936      | 0.7799   |
| 0.3869        | 2.0   | 938  | 0.4545          | 0.8995      | 0.7229      | 0.7710   | 0.8739   | 0.8303 | 0.7913 | 0.8278             | 0.8128          | 0.8145      | 0.8108   |
| 0.3825        | 3.0   | 1407 | 0.3678          | 0.8429      | 0.8191      | 0.8855   | 0.7586   | 0.8637 | 0.7877 | 0.8333             | 0.834           | 0.8329      | 0.8257   |
| 0.2683        | 4.0   | 1876 | 0.3977          | 0.8721      | 0.8029      | 0.8633   | 0.8148   | 0.8677 | 0.8088 | 0.8440             | 0.8436          | 0.8438      | 0.8382   |
| 0.2297        | 5.0   | 2345 | 0.5155          | 0.8711      | 0.7937      | 0.8552   | 0.8148   | 0.8631 | 0.8041 | 0.8396             | 0.8388          | 0.8391      | 0.8336   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1