--- license: mit base_model: xlm-roberta-base tags: - generated_from_trainer datasets: - xtreme metrics: - f1 model-index: - name: xlm-roberta-base-finetuned-panx-ar results: - task: name: Token Classification type: token-classification dataset: name: xtreme type: xtreme config: PAN-X.ar split: validation args: PAN-X.ar metrics: - name: F1 type: f1 value: 0.8937845609378455 --- # xlm-roberta-base-finetuned-panx-ar This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset. It achieves the following results on the evaluation set: - Loss: 0.2109 - F1: 0.8938 ## 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: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.3671 | 1.0 | 834 | 0.2355 | 0.8350 | | 0.2041 | 2.0 | 1668 | 0.2085 | 0.8616 | | 0.1405 | 3.0 | 2502 | 0.1882 | 0.8800 | | 0.0964 | 4.0 | 3336 | 0.2028 | 0.8819 | | 0.065 | 5.0 | 4170 | 0.2109 | 0.8938 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3