---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: MRC_ER_XLM-base_syl_ViWikiFC
  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. -->

# MRC_ER_XLM-base_syl_ViWikiFC

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4375
- Exact Match: 0.8010
- F1: 0.8260

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Exact Match | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:------:|
| 0.5246        | 1.0   | 2093  | 1.9799          | 0.7751      | 0.8080 |
| 0.4175        | 2.0   | 4186  | 1.9344          | 0.7856      | 0.8126 |
| 0.3522        | 3.0   | 6279  | 2.0761          | 0.7981      | 0.8274 |
| 0.2593        | 4.0   | 8372  | 2.3028          | 0.7990      | 0.8225 |
| 0.1676        | 5.0   | 10465 | 2.4375          | 0.8010      | 0.8260 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1