--- license: mit tags: - generated_from_trainer datasets: - wikiann metrics: - f1 base_model: xlm-roberta-base model-index: - name: xlm-roberta-base-finetuned-wikiann-hi results: - task: type: token-classification name: Token Classification dataset: name: wikiann type: wikiann args: hi metrics: - type: f1 value: 1.0 name: F1 --- # xlm-roberta-base-finetuned-wikiann-hi This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the wikiann dataset. It achieves the following results on the evaluation set: - Loss: 0.3097 - F1: 1.0 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:---:| | 0.5689 | 1.0 | 209 | 0.3179 | 1.0 | | 0.2718 | 2.0 | 418 | 0.2733 | 1.0 | | 0.19 | 3.0 | 627 | 0.2560 | 1.0 | | 0.142 | 4.0 | 836 | 0.2736 | 1.0 | | 0.0967 | 5.0 | 1045 | 0.2686 | 1.0 | | 0.0668 | 6.0 | 1254 | 0.2966 | 1.0 | | 0.052 | 7.0 | 1463 | 0.3194 | 1.0 | | 0.0369 | 8.0 | 1672 | 0.3034 | 1.0 | | 0.0236 | 9.0 | 1881 | 0.3174 | 1.0 | | 0.0135 | 10.0 | 2090 | 0.3097 | 1.0 | ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1