| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| base_model: xlm-roberta-base | |
| model-index: | |
| - name: xlm-roberta-low-resource-langID-large2 | |
| 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-low-resource-langID-large2 | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0042 | |
| - Accuracy: 0.9990 | |
| - F1: 0.9990 | |
| ## 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: 1e-05 | |
| - train_batch_size: 128 | |
| - eval_batch_size: 256 | |
| - 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 | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | |
| | 0.1152 | 1.0 | 7878 | 0.0063 | 0.9986 | 0.9985 | | |
| | 0.0066 | 2.0 | 15756 | 0.0042 | 0.9990 | 0.9990 | | |
| ### Framework versions | |
| - Transformers 4.28.0 | |
| - Pytorch 2.0.0 | |
| - Datasets 2.1.0 | |
| - Tokenizers 0.13.3 | |