---
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-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-large-cased_ner

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6758
- Precision: 0.8709
- Recall: 0.8781
- F1: 0.8737
- Accuracy: 0.9135

## 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: 16
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 438  | 0.3035          | 0.8701    | 0.8816 | 0.8748 | 0.9096   |
| 0.4531        | 2.0   | 876  | 0.3008          | 0.8820    | 0.8839 | 0.8819 | 0.9197   |
| 0.2183        | 3.0   | 1314 | 0.4003          | 0.8706    | 0.8759 | 0.8715 | 0.9119   |
| 0.1254        | 4.0   | 1752 | 0.3581          | 0.8843    | 0.8912 | 0.8870 | 0.9219   |
| 0.0704        | 5.0   | 2190 | 0.4627          | 0.8668    | 0.8683 | 0.8669 | 0.9092   |
| 0.0408        | 6.0   | 2628 | 0.5183          | 0.8703    | 0.8783 | 0.8737 | 0.9144   |
| 0.0264        | 7.0   | 3066 | 0.6201          | 0.8705    | 0.8784 | 0.8738 | 0.9122   |
| 0.0092        | 8.0   | 3504 | 0.6004          | 0.8673    | 0.8766 | 0.8712 | 0.9113   |
| 0.0092        | 9.0   | 3942 | 0.6578          | 0.8716    | 0.8782 | 0.8744 | 0.9133   |
| 0.004         | 10.0  | 4380 | 0.6758          | 0.8709    | 0.8781 | 0.8737 | 0.9135   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1