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

# biobert-ner-finetuned

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0894
- Precision: 0.9293
- Recall: 0.9551
- F1: 0.9420
- Accuracy: 0.9795

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 306  | 0.2575          | 0.7864    | 0.8034 | 0.7948 | 0.9322   |
| 0.8692        | 2.0   | 612  | 0.0949          | 0.9170    | 0.9451 | 0.9308 | 0.9759   |
| 0.8692        | 3.0   | 918  | 0.0854          | 0.9234    | 0.9607 | 0.9417 | 0.9791   |
| 0.1096        | 4.0   | 1224 | 0.0768          | 0.9333    | 0.9585 | 0.9457 | 0.9809   |
| 0.0656        | 5.0   | 1530 | 0.0772          | 0.9320    | 0.9562 | 0.9439 | 0.9806   |
| 0.0656        | 6.0   | 1836 | 0.0810          | 0.9360    | 0.9575 | 0.9466 | 0.9806   |
| 0.0468        | 7.0   | 2142 | 0.0827          | 0.9308    | 0.9580 | 0.9442 | 0.9803   |
| 0.0468        | 8.0   | 2448 | 0.0890          | 0.9248    | 0.9568 | 0.9405 | 0.9788   |
| 0.038         | 9.0   | 2754 | 0.0859          | 0.9345    | 0.9579 | 0.9460 | 0.9806   |
| 0.031         | 10.0  | 3060 | 0.0894          | 0.9293    | 0.9551 | 0.9420 | 0.9795   |


### Framework versions

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