| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bert_finetuned_ner_b |
| | 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_finetuned_ner_b |
| | |
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4684 |
| | - Precision: 0.9637 |
| | - Recall: 0.8694 |
| | - F1: 0.9141 |
| | - Accuracy: 0.9707 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | 0.0073 | 1.0 | 32820 | 0.4230 | 0.9568 | 0.8651 | 0.9086 | 0.9700 | |
| | | 0.0037 | 2.0 | 65640 | 0.4553 | 0.9618 | 0.8690 | 0.9130 | 0.9707 | |
| | | 0.0004 | 3.0 | 98460 | 0.4684 | 0.9637 | 0.8694 | 0.9141 | 0.9707 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.36.2 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| | |
