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---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-papsmear
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: 0.8088235294117647
---
<!-- 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. -->
# convnext-tiny-224-finetuned-papsmear
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: 0.4893
- Accuracy: 0.8088
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.706 | 0.9935 | 38 | 1.6028 | 0.2794 |
| 1.3867 | 1.9869 | 76 | 1.2961 | 0.4853 |
| 1.0784 | 2.9804 | 114 | 1.0588 | 0.5221 |
| 0.9128 | 4.0 | 153 | 0.8886 | 0.6618 |
| 0.7466 | 4.9935 | 191 | 0.8913 | 0.6029 |
| 0.6886 | 5.9869 | 229 | 0.7380 | 0.7059 |
| 0.6198 | 6.9804 | 267 | 0.7622 | 0.7132 |
| 0.6001 | 8.0 | 306 | 0.7083 | 0.6838 |
| 0.5542 | 8.9935 | 344 | 0.5909 | 0.7721 |
| 0.5161 | 9.9869 | 382 | 0.5909 | 0.7574 |
| 0.4631 | 10.9804 | 420 | 0.5677 | 0.7721 |
| 0.4284 | 12.0 | 459 | 0.5229 | 0.7868 |
| 0.4334 | 12.9935 | 497 | 0.5160 | 0.8015 |
| 0.4386 | 13.9869 | 535 | 0.4788 | 0.8015 |
| 0.3728 | 14.9020 | 570 | 0.4893 | 0.8088 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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