metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-large-patch16-224-dungeons-001
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: 0.75
vit-large-patch16-224-dungeons-001
This model is a fine-tuned version of google/vit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6325
- Accuracy: 0.75
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 85
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8218 | 6.6667 | 10 | 1.8564 | 0.1667 |
| 1.4325 | 13.3333 | 20 | 1.7325 | 0.3333 |
| 0.8869 | 20.0 | 30 | 1.5186 | 0.4167 |
| 0.3717 | 26.6667 | 40 | 1.1131 | 0.6667 |
| 0.0945 | 33.3333 | 50 | 0.8408 | 0.75 |
| 0.0175 | 40.0 | 60 | 0.7224 | 0.75 |
| 0.0051 | 46.6667 | 70 | 0.6674 | 0.75 |
| 0.0024 | 53.3333 | 80 | 0.6325 | 0.75 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1