---
library_name: transformers
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: mtl-xlmr-base-viwiki-v3
  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. -->

# mtl-xlmr-base-viwiki-v3

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: 0.6780

## 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: 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: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8769        | 1.0   | 960  | 0.7713          |
| 0.5802        | 2.0   | 1920 | 0.6602          |
| 0.7036        | 3.0   | 2880 | 0.6153          |
| 0.4554        | 4.0   | 3840 | 0.6017          |
| 0.3767        | 5.0   | 4800 | 0.6026          |
| 0.3122        | 6.0   | 5760 | 0.6543          |
| 0.2951        | 7.0   | 6720 | 0.6342          |
| 0.2424        | 8.0   | 7680 | 0.6403          |
| 0.3225        | 9.0   | 8640 | 0.6522          |
| 0.2981        | 10.0  | 9600 | 0.6780          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.1
- Datasets 2.21.0
- Tokenizers 0.19.1