---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- indonlu
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment_model_3
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: indonlu
      type: indonlu
      config: smsa
      split: validation
      args: smsa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9468253968253968
    - name: Precision
      type: precision
      value: 0.9299064000831855
    - name: Recall
      type: recall
      value: 0.9226916056718601
    - name: F1
      type: f1
      value: 0.9257234652270979
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# sentiment_model_3

This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on the indonlu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2301
- Accuracy: 0.9468
- Precision: 0.9299
- Recall: 0.9227
- F1: 0.9257

## 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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2455        | 1.0   | 688  | 0.1740          | 0.9476   | 0.9138    | 0.9366 | 0.9246 |
| 0.1266        | 2.0   | 1376 | 0.1898          | 0.9516   | 0.9388    | 0.9284 | 0.9332 |
| 0.0717        | 3.0   | 2064 | 0.2301          | 0.9468   | 0.9299    | 0.9227 | 0.9257 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3