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

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3723
- Precision: 0.5534
- Recall: 0.5362
- F1: 0.5447
- Accuracy: 0.9281

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 121  | 0.4063          | 0.2711    | 0.2638 | 0.2674 | 0.8968   |
| No log        | 2.0   | 242  | 0.3501          | 0.4935    | 0.3220 | 0.3897 | 0.9196   |
| No log        | 3.0   | 363  | 0.2928          | 0.4839    | 0.4255 | 0.4528 | 0.9272   |
| No log        | 4.0   | 484  | 0.3419          | 0.5407    | 0.3957 | 0.4570 | 0.9247   |
| 0.3258        | 5.0   | 605  | 0.3310          | 0.5431    | 0.4553 | 0.4954 | 0.9294   |
| 0.3258        | 6.0   | 726  | 0.3424          | 0.5248    | 0.4809 | 0.5019 | 0.9274   |
| 0.3258        | 7.0   | 847  | 0.3587          | 0.5471    | 0.5191 | 0.5328 | 0.9309   |
| 0.3258        | 8.0   | 968  | 0.3639          | 0.5396    | 0.5220 | 0.5306 | 0.9281   |
| 0.1033        | 9.0   | 1089 | 0.3695          | 0.5471    | 0.5277 | 0.5372 | 0.9276   |
| 0.1033        | 10.0  | 1210 | 0.3723          | 0.5534    | 0.5362 | 0.5447 | 0.9281   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1