---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner4
  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-ner4

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: 0.1642
- Precision: 0.3590
- Recall: 0.5245
- F1: 0.4262
- Accuracy: 0.9491

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2799        | 1.0   | 2489  | 0.2542          | 0.1535    | 0.3218 | 0.2078 | 0.9191   |
| 0.2266        | 2.0   | 4978  | 0.2269          | 0.1841    | 0.3946 | 0.2511 | 0.9255   |
| 0.2033        | 3.0   | 7467  | 0.2130          | 0.1889    | 0.4095 | 0.2585 | 0.9272   |
| 0.1799        | 4.0   | 9956  | 0.2015          | 0.1975    | 0.4561 | 0.2756 | 0.9267   |
| 0.18          | 5.0   | 12445 | 0.1995          | 0.2402    | 0.4270 | 0.3075 | 0.9387   |
| 0.1561        | 6.0   | 14934 | 0.1790          | 0.2731    | 0.4161 | 0.3298 | 0.9434   |
| 0.1503        | 7.0   | 17423 | 0.1663          | 0.3237    | 0.5351 | 0.4034 | 0.9451   |
| 0.1452        | 8.0   | 19912 | 0.1742          | 0.3319    | 0.5211 | 0.4055 | 0.9472   |
| 0.1429        | 9.0   | 22401 | 0.1654          | 0.3515    | 0.5478 | 0.4282 | 0.9479   |
| 0.1361        | 10.0  | 24890 | 0.1642          | 0.3590    | 0.5245 | 0.4262 | 0.9491   |


### Framework versions

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