1.6 KiB
1.6 KiB
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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