| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: bert-base-uncased-finetuned-ner-kmeans | |
| 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. --> | |
| # bert-base-uncased-finetuned-ner-kmeans | |
| This model is a fine-tuned version of [ArBert/bert-base-uncased-finetuned-ner](https://huggingface.co/ArBert/bert-base-uncased-finetuned-ner) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1169 | |
| - Precision: 0.9084 | |
| - Recall: 0.9245 | |
| - F1: 0.9164 | |
| - Accuracy: 0.9792 | |
| ## 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: 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 | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.036 | 1.0 | 1123 | 0.1010 | 0.9086 | 0.9117 | 0.9101 | 0.9779 | | |
| | 0.0214 | 2.0 | 2246 | 0.1094 | 0.9033 | 0.9199 | 0.9115 | 0.9784 | | |
| | 0.014 | 3.0 | 3369 | 0.1169 | 0.9084 | 0.9245 | 0.9164 | 0.9792 | | |
| ### Framework versions | |
| - Transformers 4.16.2 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 1.18.3 | |
| - Tokenizers 0.11.0 | |