metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: >-
beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled
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: 0.9765227021040974
beit-large-patch16-224-finetuned-LungCancer-Classification-LC25000-AH-40-30-30-Shuffled
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0600
- Accuracy: 0.9765
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1531 | 0.99 | 93 | 0.1351 | 0.9506 |
| 0.2389 | 1.99 | 187 | 0.1534 | 0.9344 |
| 0.2517 | 3.0 | 281 | 0.1484 | 0.9402 |
| 0.1769 | 4.0 | 375 | 0.1108 | 0.9570 |
| 0.0764 | 4.96 | 465 | 0.0600 | 0.9765 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3