---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-cti
  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-cti

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1001
- Precision: 0.9730
- Recall: 0.9844
- F1: 0.9787
- Accuracy: 0.9852

## 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: 2e-05
- train_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0346        | 1.0   | 1725  | 0.0779          | 0.9603    | 0.9788 | 0.9695 | 0.9812   |
| 0.0271        | 2.0   | 3450  | 0.0840          | 0.9588    | 0.9811 | 0.9698 | 0.9815   |
| 0.026         | 3.0   | 5175  | 0.0718          | 0.9686    | 0.9812 | 0.9748 | 0.9836   |
| 0.018         | 4.0   | 6900  | 0.0749          | 0.9687    | 0.9828 | 0.9757 | 0.9841   |
| 0.0136        | 5.0   | 8625  | 0.0872          | 0.9702    | 0.9838 | 0.9770 | 0.9847   |
| 0.0085        | 6.0   | 10350 | 0.0932          | 0.9682    | 0.9833 | 0.9757 | 0.9838   |
| 0.0075        | 7.0   | 12075 | 0.0906          | 0.9741    | 0.9836 | 0.9788 | 0.9852   |
| 0.0051        | 8.0   | 13800 | 0.0951          | 0.9727    | 0.9836 | 0.9781 | 0.9849   |
| 0.0034        | 9.0   | 15525 | 0.0990          | 0.9732    | 0.9846 | 0.9789 | 0.9851   |
| 0.0027        | 10.0  | 17250 | 0.1001          | 0.9730    | 0.9844 | 0.9787 | 0.9852   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0