---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: dinov2-base-finetuned-Leukemia
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 1.0
    - name: F1
      type: f1
      value: 1.0
---

<!-- 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. -->

# dinov2-base-finetuned-Leukemia

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- F1: 1.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.0541        | 0.9954 | 162  | 0.8475          | 0.9018   | 0.9047 |
| 0.0667        | 1.9969 | 325  | 0.0745          | 0.9785   | 0.9780 |
| 0.1317        | 2.9985 | 488  | 0.0159          | 0.9939   | 0.9939 |
| 0.0187        | 4.0    | 651  | 0.0771          | 0.9877   | 0.9878 |
| 0.0762        | 4.9954 | 813  | 0.1135          | 0.9877   | 0.9878 |
| 0.006         | 5.9969 | 976  | 0.0502          | 0.9969   | 0.9969 |
| 0.1322        | 6.9985 | 1139 | 0.0357          | 0.9969   | 0.9969 |
| 0.0332        | 8.0    | 1302 | 0.0000          | 1.0      | 1.0    |
| 0.0           | 8.9954 | 1464 | 0.0004          | 1.0      | 1.0    |
| 0.0           | 9.9539 | 1620 | 0.0000          | 1.0      | 1.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1