| license: mit | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: roberta-finetuned-ner | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # roberta-finetuned-ner | |
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1322 | |
| - Precision: 0.9772 | |
| - Recall: 0.9782 | |
| - F1: 0.9777 | |
| - Accuracy: 0.9767 | |
| ## 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: 8 | |
| - eval_batch_size: 8 | |
| - 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 | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | No log | 1.0 | 253 | 0.1694 | 0.9636 | 0.9555 | 0.9595 | 0.9617 | | |
| | 0.4479 | 2.0 | 506 | 0.1374 | 0.9743 | 0.9762 | 0.9752 | 0.9743 | | |
| | 0.4479 | 3.0 | 759 | 0.1322 | 0.9772 | 0.9782 | 0.9777 | 0.9767 | | |
| ### Framework versions | |
| - Transformers 4.17.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 2.0.0 | |
| - Tokenizers 0.11.6 | |