---
base_model: bert-base-cased
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
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: 0.1250
- Precision: 0.5977
- Recall: 0.7121
- F1: 0.6499
- Accuracy: 0.9640

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2424        | 1.0   | 2489  | 0.2411          | 0.1538    | 0.3948 | 0.2214 | 0.9097   |
| 0.1952        | 2.0   | 4978  | 0.2152          | 0.2033    | 0.4518 | 0.2804 | 0.9223   |
| 0.1771        | 3.0   | 7467  | 0.1737          | 0.2826    | 0.4268 | 0.3401 | 0.9387   |
| 0.1404        | 4.0   | 9956  | 0.1531          | 0.3981    | 0.5237 | 0.4524 | 0.9479   |
| 0.126         | 5.0   | 12445 | 0.1395          | 0.4761    | 0.6188 | 0.5382 | 0.9542   |
| 0.1084        | 6.0   | 14934 | 0.1339          | 0.4772    | 0.6758 | 0.5594 | 0.9555   |
| 0.0981        | 7.0   | 17423 | 0.1353          | 0.5228    | 0.6861 | 0.5934 | 0.9591   |
| 0.0865        | 8.0   | 19912 | 0.1308          | 0.5924    | 0.6871 | 0.6363 | 0.9628   |
| 0.0826        | 9.0   | 22401 | 0.1250          | 0.5897    | 0.7126 | 0.6453 | 0.9630   |
| 0.0754        | 10.0  | 24890 | 0.1250          | 0.5977    | 0.7121 | 0.6499 | 0.9640   |


### Framework versions

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