metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: UL_interior_classification
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: 0.5875912408759124
UL_interior_classification
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: 1.2517
- Accuracy: 0.5876
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
- 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: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7547 | 0.9811 | 13 | 2.3422 | 0.3285 |
| 1.7119 | 1.9623 | 26 | 1.8850 | 0.4964 |
| 1.249 | 2.9434 | 39 | 1.5653 | 0.5292 |
| 0.8838 | 4.0 | 53 | 1.3675 | 0.5693 |
| 0.8896 | 4.9811 | 66 | 1.2907 | 0.5803 |
| 0.7262 | 5.9623 | 79 | 1.2625 | 0.5803 |
| 0.6817 | 6.8679 | 91 | 1.2517 | 0.5876 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1