---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-grammar-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-uncased-grammar-ner

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1052
- Accuracy: 0.9895
- F1 Macro: 0.7899
- F1 Micro: 0.9212
- Precision Macro: 0.8429
- Precision Micro: 0.9694
- Recall Macro: 0.7572
- Recall Micro: 0.8776

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | Precision Macro | Precision Micro | Recall Macro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:---------------:|:------------:|:------------:|
| 0.3673        | 1.0   | 93   | 0.2453          | 0.9284   | 0.1919   | 0.4850   | 0.2701          | 0.4678          | 0.1872       | 0.5035       |
| 0.2176        | 2.0   | 186  | 0.1888          | 0.9439   | 0.2591   | 0.5149   | 0.3936          | 0.6230          | 0.2298       | 0.4388       |
| 0.1418        | 3.0   | 279  | 0.1454          | 0.9666   | 0.3554   | 0.725    | 0.4120          | 0.7902          | 0.3577       | 0.6697       |
| 0.0859        | 4.0   | 372  | 0.1238          | 0.9750   | 0.4365   | 0.7789   | 0.6084          | 0.8540          | 0.3946       | 0.7159       |
| 0.0607        | 5.0   | 465  | 0.1136          | 0.9766   | 0.4979   | 0.7965   | 0.5945          | 0.8606          | 0.4781       | 0.7413       |
| 0.0413        | 6.0   | 558  | 0.1103          | 0.9827   | 0.4995   | 0.8608   | 0.6097          | 0.9629          | 0.4415       | 0.7783       |
| 0.0309        | 7.0   | 651  | 0.1109          | 0.9821   | 0.5654   | 0.8558   | 0.6379          | 0.8842          | 0.5439       | 0.8291       |
| 0.0237        | 8.0   | 744  | 0.1056          | 0.9847   | 0.6330   | 0.8721   | 0.7169          | 0.9227          | 0.5923       | 0.8268       |
| 0.0154        | 9.0   | 837  | 0.1009          | 0.9858   | 0.6639   | 0.8816   | 0.7079          | 0.9352          | 0.6422       | 0.8337       |
| 0.0096        | 10.0  | 930  | 0.1003          | 0.9881   | 0.6783   | 0.9047   | 0.7250          | 0.9470          | 0.6494       | 0.8661       |
| 0.0078        | 11.0  | 1023 | 0.1000          | 0.9889   | 0.7661   | 0.9144   | 0.8075          | 0.9571          | 0.7524       | 0.8753       |
| 0.0052        | 12.0  | 1116 | 0.1046          | 0.9890   | 0.7563   | 0.9166   | 0.7940          | 0.9619          | 0.7561       | 0.8753       |
| 0.0041        | 13.0  | 1209 | 0.1022          | 0.9892   | 0.7804   | 0.9177   | 0.8255          | 0.9644          | 0.7570       | 0.8753       |
| 0.0021        | 14.0  | 1302 | 0.0994          | 0.9887   | 0.7602   | 0.9133   | 0.7959          | 0.9547          | 0.7534       | 0.8753       |
| 0.0018        | 15.0  | 1395 | 0.1043          | 0.9895   | 0.7903   | 0.9212   | 0.8431          | 0.9694          | 0.7572       | 0.8776       |
| 0.0016        | 16.0  | 1488 | 0.1059          | 0.9898   | 0.7901   | 0.9235   | 0.8434          | 0.9744          | 0.7572       | 0.8776       |
| 0.0014        | 17.0  | 1581 | 0.1063          | 0.9898   | 0.7924   | 0.9235   | 0.8472          | 0.9744          | 0.7572       | 0.8776       |
| 0.001         | 18.0  | 1674 | 0.1052          | 0.9895   | 0.7899   | 0.9212   | 0.8429          | 0.9694          | 0.7572       | 0.8776       |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3