--- license: mit base_model: xlm-roberta-large tags: - generated_from_trainer datasets: - shipping_label_ner model-index: - name: ner_roberta_model results: [] --- # ner_roberta_model This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the shipping_label_ner dataset. It achieves the following results on the evaluation set: - eval_loss: 0.0031 - eval_precision: 1.0 - eval_recall: 1.0 - eval_f1: 1.0 - eval_accuracy: 1.0 - eval_runtime: 0.3242 - eval_samples_per_second: 15.424 - eval_steps_per_second: 9.255 - epoch: 23.0 - step: 230 ## 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: 4 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Framework versions - Transformers 4.39.1 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2