metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-RU5-10-8
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7833333333333333
vit-base-patch16-224-RU5-10-8
This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6773
- Accuracy: 0.7833
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: 5.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3605 | 0.95 | 14 | 1.2370 | 0.5167 |
| 1.2314 | 1.97 | 29 | 1.0511 | 0.6833 |
| 0.968 | 2.98 | 44 | 0.8919 | 0.65 |
| 0.8135 | 4.0 | 59 | 0.7702 | 0.7667 |
| 0.616 | 4.95 | 73 | 0.7533 | 0.75 |
| 0.5167 | 5.97 | 88 | 0.6773 | 0.7833 |
| 0.4063 | 6.98 | 103 | 0.6974 | 0.75 |
| 0.3401 | 8.0 | 118 | 0.7438 | 0.75 |
| 0.3007 | 8.95 | 132 | 0.6646 | 0.7833 |
| 0.3154 | 9.49 | 140 | 0.6819 | 0.7833 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0