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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/deit-base-patch16-224
datasets:
- medmnist-v2
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: breastmnist-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. -->
# breastmnist-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: 0.3454
- Accuracy: 0.8718
- Precision: 0.8698
- Recall: 0.7920
- F1: 0.8194
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 0.9143 | 8 | 0.5026 | 0.7436 | 0.8701 | 0.5238 | 0.4708 |
| 0.6168 | 1.9429 | 17 | 0.4762 | 0.8462 | 0.8286 | 0.7594 | 0.7833 |
| 0.5954 | 2.9714 | 26 | 0.5305 | 0.7308 | 0.3654 | 0.5 | 0.4222 |
| 0.5934 | 4.0 | 35 | 0.4790 | 0.7692 | 0.7836 | 0.5865 | 0.5846 |
| 0.526 | 4.9143 | 43 | 0.3693 | 0.8718 | 0.8698 | 0.7920 | 0.8194 |
| 0.4651 | 5.9429 | 52 | 0.4789 | 0.7949 | 0.7434 | 0.7694 | 0.7534 |
| 0.493 | 6.9714 | 61 | 0.4187 | 0.8205 | 0.7792 | 0.7419 | 0.7565 |
| 0.4337 | 8.0 | 70 | 0.3600 | 0.8590 | 0.8417 | 0.7832 | 0.8051 |
| 0.4337 | 8.9143 | 78 | 0.3468 | 0.8718 | 0.8544 | 0.8070 | 0.8260 |
| 0.418 | 9.1429 | 80 | 0.3454 | 0.8718 | 0.8698 | 0.7920 | 0.8194 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |