transformers tf bert token-classification generated_from_keras_callback dataset:ncbi_disease base_model:google-bert/bert-base-cased base_model:finetune:google-bert/bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: bert-base-cased
datasets:
- ncbi_disease
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_keras_callback
model-index:
- name: Naveengo/bert-finetuned-on-ncbi__disease
  results: []
---

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# Naveengo/bert-finetuned-on-ncbi__disease

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on a ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0209
- Validation Loss: 0.0649
- Train Accuracy: 0.9828
- 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': '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 | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.1255     | 0.0659          | 0.9788         | 0     |
| 0.0391     | 0.0594          | 0.9821         | 1     |
| 0.0209     | 0.0649          | 0.9828         | 2     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1