---
library_name: transformers
license: mit
base_model: xlnet/xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlnet-base-cased-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. -->

# xlnet-base-cased-grammar-ner

This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1027
- Accuracy: 0.9879
- F1 Macro: 0.7899
- F1 Micro: 0.9048
- Precision Macro: 0.8321
- Precision Micro: 0.9436
- Recall Macro: 0.7769
- Recall Micro: 0.8691

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:---------------:|:------------:|:------------:|
| 0.3654        | 1.0   | 93   | 0.2315          | 0.9329   | 0.2241   | 0.4091   | 0.2338          | 0.5016          | 0.2436       | 0.3454       |
| 0.1834        | 2.0   | 186  | 0.1603          | 0.9627   | 0.2982   | 0.6748   | 0.4007          | 0.8441          | 0.2733       | 0.5621       |
| 0.1161        | 3.0   | 279  | 0.1472          | 0.9649   | 0.4016   | 0.7249   | 0.4585          | 0.7494          | 0.3910       | 0.7020       |
| 0.0764        | 4.0   | 372  | 0.1233          | 0.9739   | 0.4844   | 0.7783   | 0.5824          | 0.8346          | 0.4487       | 0.7291       |
| 0.0561        | 5.0   | 465  | 0.1224          | 0.9738   | 0.4467   | 0.7792   | 0.5923          | 0.8650          | 0.4044       | 0.7088       |
| 0.0423        | 6.0   | 558  | 0.1135          | 0.9799   | 0.6021   | 0.8375   | 0.6885          | 0.8825          | 0.5619       | 0.7968       |
| 0.0319        | 7.0   | 651  | 0.0987          | 0.9820   | 0.6386   | 0.8541   | 0.6928          | 0.8841          | 0.6342       | 0.8262       |
| 0.0221        | 8.0   | 744  | 0.1034          | 0.9836   | 0.6463   | 0.8623   | 0.7605          | 0.9184          | 0.6045       | 0.8126       |
| 0.0175        | 9.0   | 837  | 0.0984          | 0.9852   | 0.6852   | 0.8794   | 0.7154          | 0.9045          | 0.6849       | 0.8555       |
| 0.0094        | 10.0  | 930  | 0.0985          | 0.9865   | 0.6985   | 0.8936   | 0.7434          | 0.9272          | 0.6914       | 0.8623       |
| 0.0078        | 11.0  | 1023 | 0.0987          | 0.9858   | 0.7314   | 0.8876   | 0.7563          | 0.9119          | 0.7406       | 0.8646       |
| 0.0056        | 12.0  | 1116 | 0.1051          | 0.9868   | 0.7501   | 0.8923   | 0.7955          | 0.9270          | 0.7410       | 0.8600       |
| 0.0047        | 13.0  | 1209 | 0.1027          | 0.9866   | 0.7606   | 0.8936   | 0.8116          | 0.9272          | 0.7469       | 0.8623       |
| 0.0031        | 14.0  | 1302 | 0.1009          | 0.9866   | 0.7762   | 0.8953   | 0.8034          | 0.9233          | 0.7769       | 0.8691       |
| 0.0027        | 15.0  | 1395 | 0.1008          | 0.9873   | 0.7763   | 0.8995   | 0.8073          | 0.9322          | 0.7769       | 0.8691       |
| 0.002         | 16.0  | 1488 | 0.1034          | 0.9884   | 0.7939   | 0.9067   | 0.8590          | 0.9505          | 0.7591       | 0.8668       |
| 0.0015        | 17.0  | 1581 | 0.1020          | 0.9881   | 0.7925   | 0.9059   | 0.8362          | 0.9459          | 0.7769       | 0.8691       |
| 0.0016        | 18.0  | 1674 | 0.1027          | 0.9879   | 0.7899   | 0.9048   | 0.8321          | 0.9436          | 0.7769       | 0.8691       |


### Framework versions

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