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---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-pretraining-2024_03_25-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: 0.7648975791433892
---
<!-- 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_03_25-classifier
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5083
- Accuracy: 0.7649
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6422 | 1.0 | 537 | 0.6409 | 0.6560 |
| 0.5509 | 2.0 | 1074 | 0.5966 | 0.6862 |
| 0.5123 | 3.0 | 1611 | 0.5743 | 0.7044 |
| 0.5237 | 4.0 | 2148 | 0.5523 | 0.7188 |
| 0.5589 | 5.0 | 2685 | 0.5352 | 0.7370 |
| 0.5671 | 6.0 | 3222 | 0.5317 | 0.7407 |
| 0.5247 | 7.0 | 3759 | 0.5228 | 0.7486 |
| 0.4855 | 8.0 | 4296 | 0.5422 | 0.7374 |
| 0.5122 | 9.0 | 4833 | 0.5195 | 0.7477 |
| 0.5381 | 10.0 | 5370 | 0.5277 | 0.7398 |
| 0.5465 | 11.0 | 5907 | 0.5213 | 0.7514 |
| 0.4552 | 12.0 | 6444 | 0.5300 | 0.7495 |
| 0.5188 | 13.0 | 6981 | 0.5107 | 0.7505 |
| 0.5056 | 14.0 | 7518 | 0.5075 | 0.7579 |
| 0.4759 | 15.0 | 8055 | 0.5077 | 0.7644 |
| 0.6042 | 16.0 | 8592 | 0.5143 | 0.7602 |
| 0.4002 | 17.0 | 9129 | 0.5184 | 0.7612 |
| 0.4664 | 18.0 | 9666 | 0.5072 | 0.7630 |
| 0.4653 | 19.0 | 10203 | 0.5103 | 0.7626 |
| 0.4096 | 20.0 | 10740 | 0.5083 | 0.7649 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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