--- language: - mn license: mit base_model: xlm-roberta-base tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: xlm-roberta-base-ner-demo results: [] --- # xlm-roberta-base-ner-demo This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1272 - Precision: 0.9267 - Recall: 0.9350 - F1: 0.9309 - Accuracy: 0.9786 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.2011 | 1.0 | 477 | 0.0950 | 0.8951 | 0.9101 | 0.9025 | 0.9717 | | 0.0809 | 2.0 | 954 | 0.1010 | 0.8992 | 0.9135 | 0.9063 | 0.9720 | | 0.0588 | 3.0 | 1431 | 0.0937 | 0.9143 | 0.9274 | 0.9208 | 0.9765 | | 0.0438 | 4.0 | 1908 | 0.0949 | 0.9192 | 0.9291 | 0.9241 | 0.9771 | | 0.0316 | 5.0 | 2385 | 0.1000 | 0.9220 | 0.9300 | 0.9260 | 0.9771 | | 0.0238 | 6.0 | 2862 | 0.1099 | 0.9266 | 0.9333 | 0.9299 | 0.9783 | | 0.0181 | 7.0 | 3339 | 0.1125 | 0.9262 | 0.9344 | 0.9303 | 0.9783 | | 0.0135 | 8.0 | 3816 | 0.1201 | 0.9220 | 0.9333 | 0.9276 | 0.9781 | | 0.0106 | 9.0 | 4293 | 0.1244 | 0.9263 | 0.9343 | 0.9303 | 0.9784 | | 0.0089 | 10.0 | 4770 | 0.1272 | 0.9267 | 0.9350 | 0.9309 | 0.9786 | ### Framework versions - Transformers 4.35.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1