---
language:
- id
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment-lora-r2a2d0.05-0
  results: []
---

<!-- 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-lora-r2a2d0.05-0

This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3642
- Accuracy: 0.8346
- Precision: 0.7993
- Recall: 0.8080
- F1: 0.8034

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5633        | 1.0   | 122  | 0.5100          | 0.7168   | 0.6536    | 0.6446 | 0.6484 |
| 0.5083        | 2.0   | 244  | 0.4999          | 0.7243   | 0.6825    | 0.7049 | 0.6887 |
| 0.4904        | 3.0   | 366  | 0.4595          | 0.7619   | 0.7120    | 0.7065 | 0.7091 |
| 0.4644        | 4.0   | 488  | 0.4287          | 0.7920   | 0.7520    | 0.7253 | 0.7358 |
| 0.4439        | 5.0   | 610  | 0.4399          | 0.7519   | 0.7127    | 0.7395 | 0.7203 |
| 0.4241        | 6.0   | 732  | 0.4027          | 0.8221   | 0.7860    | 0.7816 | 0.7837 |
| 0.4092        | 7.0   | 854  | 0.4019          | 0.8070   | 0.7674    | 0.7835 | 0.7743 |
| 0.3891        | 8.0   | 976  | 0.3805          | 0.8271   | 0.7912    | 0.7926 | 0.7919 |
| 0.3777        | 9.0   | 1098 | 0.3789          | 0.8271   | 0.7912    | 0.7926 | 0.7919 |
| 0.369         | 10.0  | 1220 | 0.3758          | 0.8396   | 0.8071    | 0.8040 | 0.8055 |
| 0.3531        | 11.0  | 1342 | 0.3805          | 0.8296   | 0.7933    | 0.8044 | 0.7984 |
| 0.3486        | 12.0  | 1464 | 0.3801          | 0.8321   | 0.7960    | 0.8112 | 0.8027 |
| 0.3472        | 13.0  | 1586 | 0.3675          | 0.8421   | 0.8098    | 0.8083 | 0.8091 |
| 0.3379        | 14.0  | 1708 | 0.3654          | 0.8371   | 0.8032    | 0.8047 | 0.8040 |
| 0.3353        | 15.0  | 1830 | 0.3703          | 0.8421   | 0.8080    | 0.8183 | 0.8127 |
| 0.3213        | 16.0  | 1952 | 0.3709          | 0.8371   | 0.8019    | 0.8147 | 0.8077 |
| 0.3214        | 17.0  | 2074 | 0.3641          | 0.8371   | 0.8024    | 0.8097 | 0.8059 |
| 0.3225        | 18.0  | 2196 | 0.3640          | 0.8371   | 0.8024    | 0.8097 | 0.8059 |
| 0.3159        | 19.0  | 2318 | 0.3649          | 0.8346   | 0.7993    | 0.8080 | 0.8034 |
| 0.3195        | 20.0  | 2440 | 0.3642          | 0.8346   | 0.7993    | 0.8080 | 0.8034 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2