---
library_name: transformers
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: albert-base-v2-grammar-ner-generic
  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. -->

# albert-base-v2-grammar-ner-generic

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0991
- Accuracy: 0.9891
- F1 Macro: 0.9176
- F1 Micro: 0.9176
- Precision Macro: 0.9647
- Precision Micro: 0.9647
- Recall Macro: 0.875
- Recall Micro: 0.875

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:---------------:|:------------:|:------------:|
| 0.244         | 1.0   | 93   | 0.1830          | 0.9305   | 0.2897   | 0.2897   | 0.3892          | 0.3892          | 0.2308       | 0.2308       |
| 0.1652        | 2.0   | 186  | 0.1476          | 0.9450   | 0.4236   | 0.4236   | 0.6644          | 0.6644          | 0.3109       | 0.3109       |
| 0.1119        | 3.0   | 279  | 0.1070          | 0.9656   | 0.6759   | 0.6759   | 0.7313          | 0.7313          | 0.6282       | 0.6282       |
| 0.0629        | 4.0   | 372  | 0.0884          | 0.9751   | 0.7764   | 0.7764   | 0.8453          | 0.8453          | 0.7179       | 0.7179       |
| 0.0408        | 5.0   | 465  | 0.0954          | 0.9748   | 0.7911   | 0.7911   | 0.7873          | 0.7873          | 0.7949       | 0.7949       |
| 0.028         | 6.0   | 558  | 0.0830          | 0.9799   | 0.8143   | 0.8143   | 0.9194          | 0.9194          | 0.7308       | 0.7308       |
| 0.0185        | 7.0   | 651  | 0.0756          | 0.9831   | 0.8700   | 0.8700   | 0.8714          | 0.8714          | 0.8686       | 0.8686       |
| 0.0125        | 8.0   | 744  | 0.0815          | 0.9841   | 0.8591   | 0.8591   | 0.9134          | 0.9134          | 0.8109       | 0.8109       |
| 0.0073        | 9.0   | 837  | 0.0809          | 0.9854   | 0.8773   | 0.8773   | 0.8963          | 0.8963          | 0.8590       | 0.8590       |
| 0.0046        | 10.0  | 930  | 0.0895          | 0.9870   | 0.8908   | 0.8908   | 0.9526          | 0.9526          | 0.8365       | 0.8365       |
| 0.0022        | 11.0  | 1023 | 0.0903          | 0.9867   | 0.8972   | 0.8972   | 0.9136          | 0.9136          | 0.8814       | 0.8814       |
| 0.0009        | 12.0  | 1116 | 0.0957          | 0.9889   | 0.9130   | 0.9130   | 0.9545          | 0.9545          | 0.875        | 0.875        |
| 0.0005        | 13.0  | 1209 | 0.0931          | 0.9891   | 0.9149   | 0.9149   | 0.9547          | 0.9547          | 0.8782       | 0.8782       |
| 0.0002        | 14.0  | 1302 | 0.0978          | 0.9891   | 0.9176   | 0.9176   | 0.9647          | 0.9647          | 0.875        | 0.875        |
| 0.0001        | 15.0  | 1395 | 0.0982          | 0.9891   | 0.9176   | 0.9176   | 0.9647          | 0.9647          | 0.875        | 0.875        |
| 0.0           | 16.0  | 1488 | 0.0986          | 0.9889   | 0.9161   | 0.9161   | 0.9613          | 0.9613          | 0.875        | 0.875        |
| 0.0           | 17.0  | 1581 | 0.0990          | 0.9891   | 0.9176   | 0.9176   | 0.9647          | 0.9647          | 0.875        | 0.875        |
| 0.0           | 18.0  | 1674 | 0.0991          | 0.9891   | 0.9176   | 0.9176   | 0.9647          | 0.9647          | 0.875        | 0.875        |


### Framework versions

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