---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_keras_callback
model-index:
- name: Kikia26/FineTunePubMedBertWithTensorflowKeras
  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. -->

# Kikia26/FineTunePubMedBertWithTensorflowKeras

This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3522
- Validation Loss: 0.4051
- Train Precision: 0.5896
- Train Recall: 0.6245
- Train F1: 0.6066
- Train Accuracy: 0.8857
- Epoch: 9

## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 100, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 1.2909     | 0.7719          | 0.0             | 0.0          | 0.0      | 0.7813         | 0     |
| 0.8005     | 0.5567          | 0.4313          | 0.3776       | 0.4027   | 0.8372         | 1     |
| 0.5460     | 0.4551          | 0.5509          | 0.5823       | 0.5662   | 0.8676         | 2     |
| 0.4141     | 0.4381          | 0.5443          | 0.6477       | 0.5915   | 0.8732         | 3     |
| 0.3626     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 4     |
| 0.3591     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 5     |
| 0.3503     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 6     |
| 0.3521     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 7     |
| 0.3554     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 8     |
| 0.3522     | 0.4051          | 0.5896          | 0.6245       | 0.6066   | 0.8857         | 9     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0