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: 0.55625
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: 1.2851
- Accuracy: 0.5563
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9706 | 1.0 | 20 | 1.9258 | 0.35 |
| 1.672 | 2.0 | 40 | 1.7025 | 0.4625 |
| 1.4489 | 3.0 | 60 | 1.5581 | 0.4313 |
| 1.2031 | 4.0 | 80 | 1.4534 | 0.5 |
| 0.9503 | 5.0 | 100 | 1.3794 | 0.5 |
| 0.758 | 6.0 | 120 | 1.3283 | 0.5312 |
| 0.6021 | 7.0 | 140 | 1.3007 | 0.5125 |
| 0.4784 | 8.0 | 160 | 1.2851 | 0.5563 |
| 0.3682 | 9.0 | 180 | 1.2815 | 0.525 |
| 0.3117 | 10.0 | 200 | 1.3074 | 0.5125 |
| 0.2753 | 11.0 | 220 | 1.2945 | 0.525 |
| 0.2585 | 12.0 | 240 | 1.2903 | 0.5375 |
| 0.2483 | 13.0 | 260 | 1.2903 | 0.5437 |
| 0.245 | 14.0 | 280 | 1.2927 | 0.5375 |
| 0.2459 | 15.0 | 300 | 1.2925 | 0.5375 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1