metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- medmnist-v2
metrics:
- accuracy
- precision
- recall
- f1
base_model: facebook/deit-base-patch16-224
model-index:
- name: blood-deit-base-finetuned
results: []
blood-deit-base-finetuned
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the medmnist-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0767
- Accuracy: 0.9737
- Precision: 0.9730
- Recall: 0.9706
- F1: 0.9718
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: 0.005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4839 | 1.0 | 187 | 0.2824 | 0.8978 | 0.9057 | 0.8662 | 0.8763 |
| 0.4762 | 2.0 | 374 | 0.2146 | 0.9282 | 0.9246 | 0.9161 | 0.9186 |
| 0.3445 | 3.0 | 561 | 0.2135 | 0.9235 | 0.9244 | 0.9159 | 0.9168 |
| 0.2963 | 4.0 | 748 | 0.1647 | 0.9416 | 0.9323 | 0.9427 | 0.9346 |
| 0.3328 | 5.0 | 935 | 0.1762 | 0.9387 | 0.9323 | 0.9372 | 0.9316 |
| 0.3138 | 6.0 | 1122 | 0.1480 | 0.9439 | 0.9421 | 0.9482 | 0.9426 |
| 0.2489 | 7.0 | 1309 | 0.1134 | 0.9620 | 0.9536 | 0.9609 | 0.9563 |
| 0.193 | 8.0 | 1496 | 0.1020 | 0.9638 | 0.9666 | 0.9581 | 0.9616 |
| 0.1973 | 9.0 | 1683 | 0.0754 | 0.9749 | 0.9733 | 0.9761 | 0.9743 |
| 0.1711 | 10.0 | 1870 | 0.0533 | 0.9819 | 0.9826 | 0.9824 | 0.9825 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2