metadata
library_name: transformers
base_model: RobertZ2011/resnet-18-birb
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: klasifikasiburung_new
results: []
klasifikasiburung_new
This model is a fine-tuned version of 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