transformers tf bert token-classification generated_from_keras_callback en dataset:ncbi/ncbi_disease base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-uncased
datasets:
- ncbi/ncbi_disease
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- f1
pipeline_tag: token-classification
tags:
- generated_from_keras_callback
model-index:
- name: apriadiazriel/bert_base_ncbi
  results: []
---

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# apriadiazriel/bert_base_ncbi

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [NCBI disease](https://huggingface.co/datasets/ncbi/ncbi_disease) dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0168
- Validation Loss: 0.0518
- Precision: 0.8
- Recall: 0.8640
- F1: 0.8308
- Accuracy: 0.9860
- 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': 2e-05, 'decay_steps': 1017, '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 | Precision | Recall | F1 | Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.1130     | 0.0547          | 0.7364          | 0.7916       | 0.7630   | 0.9832         | 0     |
| 0.0335     | 0.0497          | 0.7836          | 0.8513       | 0.8161   | 0.9850         | 1     |
| 0.0213     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 2     |
| 0.0166     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 3     |
| 0.0173     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 4     |
| 0.0174     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 5     |
| 0.0168     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 6     |
| 0.0172     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 7     |
| 0.0167     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 8     |
| 0.0168     | 0.0518          | 0.8             | 0.8640       | 0.8308   | 0.9860         | 9     |


### Framework versions

- Transformers 4.48.3
- TensorFlow 2.18.0
- Datasets 3.3.1
- Tokenizers 0.21.0