---
base_model: dmis-lab/biobert-v1.1
tags:
- generated_from_keras_callback
model-index:
- name: Meli101/biobert-v1.1-sentence-classifier-tf
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# Meli101/biobert-v1.1-sentence-classifier-tf

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1155
- Validation Loss: 0.2999
- Train Precision: 0.9130
- Train Recall: 0.9134
- Train Accuracy: 0.9129
- Train F1: 0.9128
- Epoch: 2

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1535, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train Accuracy | Train F1 | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------------:|:--------:|:-----:|
| 0.5898     | 0.3387          | 0.8804          | 0.8786       | 0.8788         | 0.8788   | 0     |
| 0.2266     | 0.3110          | 0.8974          | 0.8913       | 0.8910         | 0.8903   | 1     |
| 0.1155     | 0.2999          | 0.9130          | 0.9134       | 0.9129         | 0.9128   | 2     |


### Framework versions

- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.17.1
- Tokenizers 0.15.2