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---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_keras_callback
model-index:
- name: Kikia26/FineTunePubMedBertWithTensorflowKeras3
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/FineTunePubMedBertWithTensorflowKeras3
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: 0.0981
- Validation Loss: 0.3764
- Train Precision: 0.6444
- Train Recall: 0.7342
- Train F1: 0.6864
- Train Accuracy: 0.9014
- Epoch: 12
## 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': 200, '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 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 1.4820 | 0.8904 | 0.0 | 0.0 | 0.0 | 0.7808 | 0 |
| 0.8734 | 0.6681 | 0.6159 | 0.1793 | 0.2778 | 0.8274 | 1 |
| 0.6618 | 0.5098 | 0.6180 | 0.4641 | 0.5301 | 0.8673 | 2 |
| 0.4675 | 0.4214 | 0.6199 | 0.5781 | 0.5983 | 0.8841 | 3 |
| 0.3731 | 0.3833 | 0.5849 | 0.6540 | 0.6175 | 0.8910 | 4 |
| 0.2830 | 0.3550 | 0.6019 | 0.6730 | 0.6355 | 0.8958 | 5 |
| 0.2357 | 0.3555 | 0.6137 | 0.7004 | 0.6542 | 0.9025 | 6 |
| 0.2042 | 0.3500 | 0.6325 | 0.6646 | 0.6481 | 0.9004 | 7 |
| 0.1721 | 0.3511 | 0.5891 | 0.7046 | 0.6417 | 0.8964 | 8 |
| 0.1516 | 0.3692 | 0.6264 | 0.7004 | 0.6614 | 0.9017 | 9 |
| 0.1281 | 0.3477 | 0.6508 | 0.7194 | 0.6834 | 0.9046 | 10 |
| 0.1058 | 0.3701 | 0.6232 | 0.7257 | 0.6706 | 0.9012 | 11 |
| 0.0981 | 0.3764 | 0.6444 | 0.7342 | 0.6864 | 0.9014 | 12 |
### Framework versions
- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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