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

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: 1.1769
- Accuracy: 0.7604
- Precision: 0.7654
- Recall: 0.7604
- F1: 0.7572

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.3725        | 1.0   | 375  | 2.1701          | 0.5720   | 0.6410    | 0.5720 | 0.5531 |
| 1.9971        | 2.0   | 750  | 1.7855          | 0.6595   | 0.6896    | 0.6595 | 0.6456 |
| 1.6092        | 3.0   | 1125 | 1.5948          | 0.7026   | 0.7201    | 0.7026 | 0.6921 |
| 1.5044        | 4.0   | 1500 | 1.4862          | 0.7173   | 0.7288    | 0.7173 | 0.7078 |
| 1.2893        | 5.0   | 1875 | 1.4145          | 0.7309   | 0.7402    | 0.7309 | 0.7236 |
| 1.2276        | 6.0   | 2250 | 1.3653          | 0.7373   | 0.7454    | 0.7373 | 0.7310 |
| 1.1467        | 7.0   | 2625 | 1.3099          | 0.7478   | 0.7536    | 0.7478 | 0.7420 |
| 1.0491        | 8.0   | 3000 | 1.2975          | 0.7451   | 0.7518    | 0.7451 | 0.7399 |
| 0.9231        | 9.0   | 3375 | 1.2683          | 0.7518   | 0.7574    | 0.7518 | 0.7470 |
| 0.8979        | 10.0  | 3750 | 1.2389          | 0.7561   | 0.7609    | 0.7561 | 0.7519 |
| 0.9467        | 11.0  | 4125 | 1.2400          | 0.7566   | 0.7608    | 0.7566 | 0.7517 |
| 0.8315        | 12.0  | 4500 | 1.2164          | 0.7565   | 0.7623    | 0.7565 | 0.7530 |
| 0.7316        | 13.0  | 4875 | 1.2005          | 0.7570   | 0.7612    | 0.7570 | 0.7531 |
| 0.6786        | 14.0  | 5250 | 1.2080          | 0.7560   | 0.7623    | 0.7560 | 0.7527 |
| 0.7923        | 15.0  | 5625 | 1.1869          | 0.7582   | 0.7628    | 0.7582 | 0.7545 |
| 0.7415        | 16.0  | 6000 | 1.1802          | 0.7575   | 0.7633    | 0.7575 | 0.7548 |
| 0.6292        | 17.0  | 6375 | 1.1994          | 0.7542   | 0.7602    | 0.7542 | 0.7513 |
| 0.7069        | 18.0  | 6750 | 1.1769          | 0.7604   | 0.7654    | 0.7604 | 0.7572 |
| 0.69          | 19.0  | 7125 | 1.1743          | 0.7572   | 0.7610    | 0.7572 | 0.7542 |
| 0.6476        | 20.0  | 7500 | 1.1704          | 0.7585   | 0.7638    | 0.7585 | 0.7558 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1