| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bert-base-cased-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. --> |
| |
|
| | # bert-base-cased-ner |
| |
|
| | This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3793 |
| | - Job Title precision: 0.8079 |
| | - Job Title recall: 0.8248 |
| | - Job Title f1: 0.8163 |
| | - Loc precision: 0.8911 |
| | - Loc recall: 0.9081 |
| | - Loc f1: 0.8995 |
| | - Org precision: 0.6484 |
| | - Org recall: 0.7620 |
| | - Org f1: 0.7006 |
| | - Misc precision: 0.6134 |
| | - Misc recall: 0.7201 |
| | - Misc f1: 0.6625 |
| | - Precision: 0.7800 |
| | - Recall: 0.8265 |
| | - F1: 0.8025 |
| | - Accuracy: 0.8606 |
| |
|
| | ## 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: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Job Title precision | Job Title recall | Job Title f1 | Loc precision | Loc recall | Loc f1 | Org precision | Org recall | Org f1 | Misc precision | Misc recall | Misc f1 | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|:--------------:|:-----------:|:-------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 308 | 0.3793 | 0.8079 | 0.8248 | 0.8163 | 0.8911 | 0.9081 | 0.8995 | 0.6484 | 0.7620 | 0.7006 | 0.6134 | 0.7201 | 0.6625 | 0.7800 | 0.8265 | 0.8025 | 0.8606 | |
| | | 0.4249 | 2.0 | 616 | 0.3866 | 0.7911 | 0.8728 | 0.8299 | 0.8676 | 0.9541 | 0.9088 | 0.6551 | 0.7886 | 0.7157 | 0.6623 | 0.6962 | 0.6789 | 0.7719 | 0.8669 | 0.8167 | 0.8685 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.1 |
| | - Pytorch 1.7.1+cu110 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.2 |
| |
|
