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

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1078
- Precision: 0.9466
- Recall: 0.9706
- F1: 0.9585
- Accuracy: 0.9788

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4602        | 1.0   | 612  | 0.1189          | 0.9232    | 0.9431 | 0.9330 | 0.9683   |
| 0.1394        | 2.0   | 1224 | 0.1071          | 0.9236    | 0.9702 | 0.9463 | 0.9728   |
| 0.0939        | 3.0   | 1836 | 0.0952          | 0.9445    | 0.9652 | 0.9547 | 0.9774   |
| 0.0759        | 4.0   | 2448 | 0.0968          | 0.9417    | 0.9680 | 0.9547 | 0.9770   |
| 0.0549        | 5.0   | 3060 | 0.0981          | 0.9448    | 0.9670 | 0.9558 | 0.9773   |
| 0.0481        | 6.0   | 3672 | 0.1025          | 0.9416    | 0.9706 | 0.9559 | 0.9774   |
| 0.0401        | 7.0   | 4284 | 0.1045          | 0.9407    | 0.9705 | 0.9554 | 0.9771   |
| 0.0387        | 8.0   | 4896 | 0.1042          | 0.9455    | 0.9705 | 0.9578 | 0.9784   |
| 0.0301        | 9.0   | 5508 | 0.1059          | 0.9475    | 0.9704 | 0.9588 | 0.9790   |
| 0.0286        | 10.0  | 6120 | 0.1078          | 0.9466    | 0.9706 | 0.9585 | 0.9788   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0