---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ncbi
  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-ncbi

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0584
- Precision: 0.8277
- Recall: 0.8729
- F1: 0.8497
- Accuracy: 0.9859

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1091        | 1.0   | 680  | 0.0479          | 0.7906    | 0.8539 | 0.8210 | 0.9836   |
| 0.0338        | 2.0   | 1360 | 0.0484          | 0.7998    | 0.8679 | 0.8324 | 0.9852   |
| 0.0128        | 3.0   | 2040 | 0.0584          | 0.8277    | 0.8729 | 0.8497 | 0.9859   |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2