---
license: mit
base_model: papluca/xlm-roberta-base-language-detection
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: xlm-roberta-base-language-detection-disaster-twitter
  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. -->

# xlm-roberta-base-language-detection-disaster-twitter

This model is a fine-tuned version of [papluca/xlm-roberta-base-language-detection](https://huggingface.co/papluca/xlm-roberta-base-language-detection) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4869
- F1: 0.7902

## 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 381  | 0.4407          | 0.7701 |
| 0.4972        | 2.0   | 762  | 0.4186          | 0.7560 |
| 0.3742        | 3.0   | 1143 | 0.4869          | 0.7902 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2+cpu
- Datasets 2.1.0
- Tokenizers 0.15.2