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---
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
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