|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: xlm-roberta-base-language-detection |
|
results: [] |
|
--- |
|
|
|
# xlm-roberta-base-language-detection |
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the [Language Identification](https://huggingface.co/datasets/papluca/language-identification#additional-information) dataset. |
|
|
|
## Intended uses & limitations |
|
|
|
You can directly use this model as a language detector, i.e. for sequence classification tasks. Currently, it supports the following 20 languages: |
|
|
|
`arabic (ar), bulgarian (bg), german (de), modern greek (el), english (en), spanish (es), french (fr), hindi (hi), italian (it), japanese (ja), dutch (nl), polish (pl), portuguese (pt), russian (ru), swahili (sw), thai (th), turkish (tr), urdu (ur), vietnamese (vi), and chinese (zh)` |
|
|
|
## Training and evaluation data |
|
|
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0103 |
|
- Accuracy: 0.9977 |
|
- F1: 0.9977 |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 2e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 2 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.2492 | 1.0 | 1094 | 0.0149 | 0.9969 | 0.9969 | |
|
| 0.0101 | 2.0 | 2188 | 0.0103 | 0.9977 | 0.9977 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.12.5 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.15.1 |
|
- Tokenizers 0.10.3 |
|
|
