license	tags	metrics	model-index
mit	generated_from_trainer	accuracy f1	name results xlm-roberta-base-language-detection

xlm-roberta-base-language-detection

This model is a fine-tuned version of xlm-roberta-base on the None 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