---
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bertNer-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. -->

# bertNer-biobert

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: 0.1284
- Precision: 0.9471
- Recall: 0.9630
- F1: 0.9550
- Accuracy: 0.9758

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1851        | 1.0   | 1224  | 0.1186          | 0.9202    | 0.9550 | 0.9373 | 0.9670   |
| 0.1188        | 2.0   | 2448  | 0.1061          | 0.9349    | 0.9684 | 0.9514 | 0.9737   |
| 0.0789        | 3.0   | 3672  | 0.1051          | 0.9381    | 0.9710 | 0.9543 | 0.9755   |
| 0.0569        | 4.0   | 4896  | 0.1062          | 0.9403    | 0.9712 | 0.9555 | 0.9761   |
| 0.0492        | 5.0   | 6120  | 0.1174          | 0.9403    | 0.9646 | 0.9523 | 0.9734   |
| 0.0405        | 6.0   | 7344  | 0.1220          | 0.9426    | 0.9638 | 0.9531 | 0.9739   |
| 0.0355        | 7.0   | 8568  | 0.1175          | 0.9446    | 0.9651 | 0.9548 | 0.9756   |
| 0.0296        | 8.0   | 9792  | 0.1239          | 0.9446    | 0.9660 | 0.9552 | 0.9757   |
| 0.0224        | 9.0   | 11016 | 0.1247          | 0.9474    | 0.9640 | 0.9556 | 0.9760   |
| 0.0219        | 10.0  | 12240 | 0.1284          | 0.9471    | 0.9630 | 0.9550 | 0.9758   |


### Framework versions

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