metadata
library_name: transformers
base_model: RobertZ2011/resnet-18-birb
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: klasifikasiburung
results: []
klasifikasiburung
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: 1.0513
- Accuracy: 0.7765
- Precision: 0.7801
- Recall: 0.7765
- F1: 0.7734
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.4823 | 1.0 | 375 | 1.3049 | 0.7365 | 0.7549 | 0.7365 | 0.7280 |
| 1.0529 | 2.0 | 750 | 1.1702 | 0.7641 | 0.7706 | 0.7641 | 0.7588 |
| 0.7485 | 3.0 | 1125 | 1.0967 | 0.7689 | 0.7780 | 0.7689 | 0.7662 |
| 0.6476 | 4.0 | 1500 | 1.0676 | 0.7717 | 0.7755 | 0.7717 | 0.7688 |
| 0.4738 | 5.0 | 1875 | 1.0513 | 0.7765 | 0.7801 | 0.7765 | 0.7734 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1