language-detection-fine-tuned-on-xlm-roberta-base
This model is a fine-tuned version of xlm-roberta-base on the common_language dataset. It achieves the following results on the evaluation set:
- Loss: 0.1527
- Accuracy: 0.9779
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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2047 | 1.0 | 22194 | 0.1527 | 0.9779 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for barto17/language-detection-fine-tuned-on-xlm-roberta-base
Base model
FacebookAI/xlm-roberta-baseDataset used to train barto17/language-detection-fine-tuned-on-xlm-roberta-base
Spaces using barto17/language-detection-fine-tuned-on-xlm-roberta-base 3
Evaluation results
- Accuracy on common_languagetest set self-reported0.978