---
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_keras_callback
model-index:
- name: damand2061/pfsa-id-med-indobert-nlu
  results: []
language:
- id
pipeline_tag: token-classification
library_name: transformers
---

<!-- 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. -->

# damand2061/pfsa-id-med-indobert-nlu

This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0536
- Validation Loss: 0.3159
- Validation F1: 0.8593
- Validation Accuracy: 0.9287
- Epoch: 4

## 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': 1e-05, 'decay_steps': 19220, '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: mixed_float16

### Training results

| Train Loss | Validation Loss | Validation F1 | Validation Accuracy | Epoch |
|:----------:|:---------------:|:-------------:|:-------------------:|:-----:|
| 0.2859     | 0.2166          | 0.8202        | 0.9290              | 0     |
| 0.1802     | 0.2188          | 0.8487        | 0.9301              | 1     |
| 0.1260     | 0.2377          | 0.8558        | 0.9281              | 2     |
| 0.0807     | 0.2802          | 0.8588        | 0.9274              | 3     |
| 0.0536     | 0.3159          | 0.8593        | 0.9287              | 4     |


### Framework versions

- Transformers 4.44.0
- TensorFlow 2.16.1
- Datasets 2.21.0
- Tokenizers 0.19.1