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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: apriadiazriel/bert_base_ncbi
results: []
datasets:
- ncbi/ncbi_disease
language:
- en
metrics:
- f1
pipeline_tag: token-classification
---
<!-- 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. -->
# 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 |