| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bert-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. --> |
| |
|
| | # bert-finetuned-ner |
| |
|
| | This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1622 |
| | - Precision: 0.7774 |
| | - Recall: 0.7937 |
| | - F1: 0.7854 |
| | - 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: 8e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 8 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 131 | 0.1355 | 0.6880 | 0.7298 | 0.7083 | 0.9604 | |
| | | No log | 2.0 | 262 | 0.1194 | 0.7564 | 0.7727 | 0.7645 | 0.9684 | |
| | | No log | 3.0 | 393 | 0.1277 | 0.7731 | 0.7868 | 0.7799 | 0.9691 | |
| | | 0.0433 | 4.0 | 524 | 0.1433 | 0.7553 | 0.7829 | 0.7688 | 0.9685 | |
| | | 0.0433 | 5.0 | 655 | 0.1515 | 0.7734 | 0.7946 | 0.7839 | 0.9700 | |
| | | 0.0433 | 6.0 | 786 | 0.1518 | 0.7819 | 0.8008 | 0.7912 | 0.9708 | |
| | | 0.0433 | 7.0 | 917 | 0.1602 | 0.7752 | 0.7914 | 0.7832 | 0.9704 | |
| | | 0.0094 | 8.0 | 1048 | 0.1622 | 0.7774 | 0.7937 | 0.7854 | 0.9707 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
