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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-large-1k-224-finetuned-LungCancer-Classification-LC25000-AH-60-20-20
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: Augmented-Final
split: train
args: Augmented-Final
metrics:
- name: Accuracy
type: accuracy
value: 0.9996666666666667
---
<!-- 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. -->
# convnextv2-large-1k-224-finetuned-LungCancer-Classification-LC25000-AH-60-20-20
This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0043
- Accuracy: 0.9997
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 0.9
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4332 | 1.0 | 281 | 0.3824 | 0.947 |
| 0.1558 | 2.0 | 563 | 0.1292 | 0.9737 |
| 0.1161 | 3.0 | 844 | 0.0556 | 0.9887 |
| 0.2337 | 4.0 | 1126 | 0.0683 | 0.982 |
| 0.1285 | 5.0 | 1407 | 0.0293 | 0.9923 |
| 0.047 | 6.0 | 1689 | 0.0987 | 0.975 |
| 0.0741 | 7.0 | 1970 | 0.0373 | 0.988 |
| 0.153 | 8.0 | 2252 | 0.0043 | 0.9997 |
| 0.0244 | 9.0 | 2533 | 0.0696 | 0.981 |
| 0.0646 | 10.0 | 2815 | 0.0120 | 0.995 |
| 0.0025 | 11.0 | 3096 | 0.0076 | 0.9977 |
| 0.0611 | 11.98 | 3372 | 0.0024 | 0.9997 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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