|
--- |
|
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: organc-deit-base-finetuned |
|
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. --> |
|
|
|
# organc-deit-base-finetuned |
|
|
|
This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the medmnist-v2 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2795 |
|
- Accuracy: 0.9240 |
|
- Precision: 0.9199 |
|
- Recall: 0.9123 |
|
- F1: 0.9154 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.7947 | 1.0 | 203 | 0.3123 | 0.8976 | 0.9090 | 0.8450 | 0.8632 | |
|
| 0.6703 | 2.0 | 406 | 0.1400 | 0.9607 | 0.9590 | 0.9543 | 0.9535 | |
|
| 0.5941 | 3.0 | 609 | 0.1182 | 0.9699 | 0.9647 | 0.9681 | 0.9649 | |
|
| 0.5837 | 4.0 | 813 | 0.1016 | 0.9678 | 0.9558 | 0.9586 | 0.9551 | |
|
| 0.5193 | 5.0 | 1016 | 0.0800 | 0.9791 | 0.9701 | 0.9684 | 0.9675 | |
|
| 0.5513 | 6.0 | 1219 | 0.0579 | 0.9862 | 0.9831 | 0.9855 | 0.9840 | |
|
| 0.4343 | 7.0 | 1422 | 0.0775 | 0.9833 | 0.9858 | 0.9818 | 0.9835 | |
|
| 0.3942 | 8.0 | 1626 | 0.0782 | 0.9833 | 0.9813 | 0.9827 | 0.9817 | |
|
| 0.2971 | 9.0 | 1829 | 0.0839 | 0.9862 | 0.9884 | 0.9866 | 0.9873 | |
|
| 0.3242 | 9.99 | 2030 | 0.0745 | 0.9870 | 0.9877 | 0.9863 | 0.9868 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
