metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
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: 0.60625
image_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1494
- Accuracy: 0.6062
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8347 | 1.0 | 10 | 1.9052 | 0.3688 |
| 1.838 | 2.0 | 20 | 1.7999 | 0.375 |
| 1.7193 | 3.0 | 30 | 1.6869 | 0.35 |
| 1.5873 | 4.0 | 40 | 1.5855 | 0.4437 |
| 1.4919 | 5.0 | 50 | 1.4977 | 0.475 |
| 1.4049 | 6.0 | 60 | 1.4425 | 0.4875 |
| 1.3025 | 7.0 | 70 | 1.4254 | 0.45 |
| 1.238 | 8.0 | 80 | 1.3994 | 0.475 |
| 1.1704 | 9.0 | 90 | 1.3109 | 0.5312 |
| 1.1009 | 10.0 | 100 | 1.3309 | 0.525 |
| 1.0309 | 11.0 | 110 | 1.2941 | 0.5687 |
| 0.9705 | 12.0 | 120 | 1.2750 | 0.5188 |
| 0.9315 | 13.0 | 130 | 1.2402 | 0.55 |
| 0.8894 | 14.0 | 140 | 1.2425 | 0.5375 |
| 0.8374 | 15.0 | 150 | 1.2273 | 0.525 |
| 0.8 | 16.0 | 160 | 1.2454 | 0.5125 |
| 0.7597 | 17.0 | 170 | 1.2445 | 0.5125 |
| 0.7143 | 18.0 | 180 | 1.1750 | 0.5687 |
| 0.6832 | 19.0 | 190 | 1.2456 | 0.525 |
| 0.6573 | 20.0 | 200 | 1.2004 | 0.5938 |
| 0.639 | 21.0 | 210 | 1.1924 | 0.5563 |
| 0.635 | 22.0 | 220 | 1.1257 | 0.6 |
| 0.5982 | 23.0 | 230 | 1.1845 | 0.575 |
| 0.5675 | 24.0 | 240 | 1.2291 | 0.5625 |
| 0.5634 | 25.0 | 250 | 1.1837 | 0.5687 |
| 0.535 | 26.0 | 260 | 1.2384 | 0.5813 |
| 0.5233 | 27.0 | 270 | 1.1911 | 0.5875 |
| 0.529 | 28.0 | 280 | 1.2083 | 0.5875 |
| 0.5141 | 29.0 | 290 | 1.1813 | 0.5875 |
| 0.5166 | 30.0 | 300 | 1.1578 | 0.5938 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3