--- license: mit base_model: xlm-roberta-base tags: - generated_from_trainer datasets: - masakhaner2 metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-wol results: - task: name: Token Classification type: token-classification dataset: name: masakhaner2 type: masakhaner2 config: wol split: validation args: wol metrics: - name: F1 type: f1 value: 0.7818981772470145 --- # xlm-roberta-base-finetuned-wol This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the masakhaner2 dataset. It achieves the following results on the evaluation set: - Loss: 0.0734 - F1: 0.7819 ## 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: 5e-05 - train_batch_size: 48 - eval_batch_size: 48 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.0 | 96 | 0.1055 | 0.6577 | | 0.1995 | 2.0 | 192 | 0.0785 | 0.7488 | | 0.1995 | 3.0 | 288 | 0.0734 | 0.7819 | ### Framework versions - Transformers 4.33.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3