---
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: finetuned-Leukemia-cell
  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: 0.9661654135338346
---

<!-- 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. -->

# finetuned-Leukemia-cell

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1249
- Accuracy: 0.9662

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3396        | 2.94  | 100  | 0.2611          | 0.9060   |
| 0.2488        | 5.88  | 200  | 0.2651          | 0.9173   |
| 0.1783        | 8.82  | 300  | 0.1906          | 0.9323   |
| 0.0837        | 11.76 | 400  | 0.1773          | 0.9511   |
| 0.0934        | 14.71 | 500  | 0.2027          | 0.9361   |
| 0.1283        | 17.65 | 600  | 0.0602          | 0.9737   |
| 0.06          | 20.59 | 700  | 0.1383          | 0.9624   |
| 0.024         | 23.53 | 800  | 0.0773          | 0.9737   |
| 0.0446        | 26.47 | 900  | 0.1669          | 0.9549   |
| 0.0342        | 29.41 | 1000 | 0.1320          | 0.9624   |
| 0.0458        | 32.35 | 1100 | 0.1128          | 0.9662   |
| 0.0394        | 35.29 | 1200 | 0.2099          | 0.9436   |
| 0.0593        | 38.24 | 1300 | 0.0890          | 0.9774   |
| 0.0346        | 41.18 | 1400 | 0.1216          | 0.9662   |
| 0.0535        | 44.12 | 1500 | 0.1303          | 0.9662   |
| 0.0139        | 47.06 | 1600 | 0.1195          | 0.9624   |
| 0.0476        | 50.0  | 1700 | 0.1249          | 0.9662   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0