---
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: 0.8089
- Precision: 0.3730
- Recall: 0.5764
- F1: 0.4529
- Accuracy: 0.7512

## 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   | 69   | 0.8052          | 0.3835    | 0.3229 | 0.3506 | 0.7630   |
| No log        | 2.0   | 138  | 0.7310          | 0.3635    | 0.4809 | 0.4141 | 0.7549   |
| No log        | 3.0   | 207  | 0.7309          | 0.3881    | 0.5208 | 0.4448 | 0.7621   |
| No log        | 4.0   | 276  | 0.7683          | 0.3926    | 0.5330 | 0.4521 | 0.7642   |
| No log        | 5.0   | 345  | 0.8089          | 0.3730    | 0.5764 | 0.4529 | 0.7512   |


### Framework versions

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