metadata
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224
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: 0.7441860465116279
vit-base-patch16-224
This model was trained from scratch on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5859
- Accuracy: 0.7442
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: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.96 | 6 | 0.5859 | 0.7442 |
| 0.605 | 1.92 | 12 | 0.5842 | 0.7442 |
| 0.605 | 2.88 | 18 | 0.5919 | 0.7442 |
| 0.5428 | 4.0 | 25 | 0.5885 | 0.7442 |
| 0.5584 | 4.96 | 31 | 0.5886 | 0.7442 |
| 0.5584 | 5.92 | 37 | 0.5915 | 0.7442 |
| 0.5593 | 6.88 | 43 | 0.5935 | 0.7442 |
| 0.5097 | 8.0 | 50 | 0.5947 | 0.7442 |
| 0.5097 | 8.96 | 56 | 0.5949 | 0.7442 |
| 0.5205 | 9.6 | 60 | 0.5949 | 0.7442 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1