---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-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-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: 0.7190
- Precision: 0.4554
- Recall: 0.5226
- F1: 0.4867
- Accuracy: 0.7739

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 51   | 1.0096          | 0.2965    | 0.0405 | 0.0713 | 0.7110   |
| No log        | 2.0   | 102  | 0.8495          | 0.3573    | 0.2883 | 0.3191 | 0.7415   |
| No log        | 3.0   | 153  | 0.7566          | 0.4296    | 0.5187 | 0.4700 | 0.7663   |
| No log        | 4.0   | 204  | 0.7221          | 0.4573    | 0.4718 | 0.4644 | 0.7706   |
| No log        | 5.0   | 255  | 0.7190          | 0.4554    | 0.5226 | 0.4867 | 0.7739   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1