---
library_name: transformers
base_model: RobertZ2011/resnet-18-birb
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: klasifikasiburung
  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. -->

# klasifikasiburung

This model is a fine-tuned version of [RobertZ2011/resnet-18-birb](https://huggingface.co/RobertZ2011/resnet-18-birb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0186
- Accuracy: 0.7565
- Precision: 0.7631
- Recall: 0.7565
- F1: 0.7554

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5955        | 1.0   | 188  | 1.4442          | 0.7235   | 0.7426    | 0.7235 | 0.7169 |
| 1.1224        | 2.0   | 376  | 1.2881          | 0.7458   | 0.7546    | 0.7458 | 0.7406 |
| 0.7778        | 3.0   | 564  | 1.1965          | 0.7501   | 0.7635    | 0.7501 | 0.7483 |
| 0.5573        | 4.0   | 752  | 1.1417          | 0.7565   | 0.7635    | 0.7565 | 0.7538 |
| 0.4231        | 5.0   | 940  | 1.1077          | 0.7584   | 0.7671    | 0.7584 | 0.7567 |
| 0.2878        | 6.0   | 1128 | 1.0893          | 0.7601   | 0.7716    | 0.7601 | 0.7597 |
| 0.2043        | 7.0   | 1316 | 1.0688          | 0.7591   | 0.7661    | 0.7591 | 0.7579 |
| 0.1326        | 8.0   | 1504 | 1.0687          | 0.7582   | 0.7653    | 0.7582 | 0.7565 |
| 0.0851        | 9.0   | 1692 | 1.0502          | 0.7598   | 0.7652    | 0.7598 | 0.7581 |
| 0.0807        | 10.0  | 1880 | 1.0318          | 0.7582   | 0.7644    | 0.7582 | 0.7569 |
| 0.0581        | 11.0  | 2068 | 1.0403          | 0.7572   | 0.7629    | 0.7572 | 0.7558 |
| 0.043         | 12.0  | 2256 | 1.0295          | 0.7565   | 0.7633    | 0.7565 | 0.7557 |
| 0.0379        | 13.0  | 2444 | 1.0271          | 0.7568   | 0.7636    | 0.7568 | 0.7557 |
| 0.0399        | 14.0  | 2632 | 1.0319          | 0.7558   | 0.7627    | 0.7558 | 0.7549 |
| 0.0447        | 15.0  | 2820 | 1.0186          | 0.7565   | 0.7631    | 0.7565 | 0.7554 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1