--- license: mit tags: - generated_from_trainer datasets: - xtreme metrics: - f1 base_model: xlm-roberta-base model-index: - name: xlm-roberta-base-finetuned-panx-it results: - task: type: token-classification name: Token Classification dataset: name: xtreme type: xtreme args: PAN-X.it metrics: - type: f1 value: 0.8289473684210525 name: F1 --- # xlm-roberta-base-finetuned-panx-it 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: 0.2403 - F1: 0.8289 ## 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: 16 - eval_batch_size: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.668 | 1.0 | 105 | 0.2886 | 0.7818 | | 0.2583 | 2.0 | 210 | 0.2421 | 0.8202 | | 0.1682 | 3.0 | 315 | 0.2403 | 0.8289 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.11.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1