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---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-pretraining-2024_04_02-atelectasis-classifier
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: 0.7644320297951583
---
<!-- 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. -->
# vit-pretraining-2024_04_02-atelectasis-classifier
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5020
- Accuracy: 0.7644
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6304 | 1.0 | 537 | 0.6342 | 0.6709 |
| 0.5931 | 2.0 | 1074 | 0.5669 | 0.7207 |
| 0.5027 | 3.0 | 1611 | 0.5397 | 0.7393 |
| 0.5659 | 4.0 | 2148 | 0.5341 | 0.7458 |
| 0.5115 | 5.0 | 2685 | 0.5433 | 0.7346 |
| 0.5108 | 6.0 | 3222 | 0.5454 | 0.7309 |
| 0.5187 | 7.0 | 3759 | 0.5136 | 0.7621 |
| 0.4435 | 8.0 | 4296 | 0.5057 | 0.7677 |
| 0.583 | 9.0 | 4833 | 0.5042 | 0.7584 |
| 0.5256 | 10.0 | 5370 | 0.5249 | 0.7495 |
| 0.4818 | 11.0 | 5907 | 0.5212 | 0.7481 |
| 0.5575 | 12.0 | 6444 | 0.5061 | 0.7481 |
| 0.3572 | 13.0 | 6981 | 0.5042 | 0.7602 |
| 0.489 | 14.0 | 7518 | 0.5004 | 0.7709 |
| 0.4773 | 15.0 | 8055 | 0.5074 | 0.7700 |
| 0.4577 | 16.0 | 8592 | 0.5054 | 0.7677 |
| 0.4619 | 17.0 | 9129 | 0.5021 | 0.7686 |
| 0.3865 | 18.0 | 9666 | 0.5074 | 0.7644 |
| 0.4889 | 19.0 | 10203 | 0.5113 | 0.7598 |
| 0.4637 | 20.0 | 10740 | 0.5020 | 0.7644 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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