metadata
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: 0.58125
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: 1.2066
- Accuracy: 0.5813
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: 2
- 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_ratio: 0.05
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0741 | 1.0 | 20 | 2.0298 | 0.2687 |
| 1.9068 | 2.0 | 40 | 1.7590 | 0.425 |
| 1.6486 | 3.0 | 60 | 1.5578 | 0.4688 |
| 1.4978 | 4.0 | 80 | 1.4362 | 0.5375 |
| 1.3643 | 5.0 | 100 | 1.3577 | 0.5312 |
| 1.2724 | 6.0 | 120 | 1.3503 | 0.5437 |
| 1.1678 | 7.0 | 140 | 1.2626 | 0.575 |
| 1.074 | 8.0 | 160 | 1.2404 | 0.5813 |
| 1.0216 | 9.0 | 180 | 1.2679 | 0.5375 |
| 0.943 | 10.0 | 200 | 1.1997 | 0.6 |
| 0.9146 | 11.0 | 220 | 1.1864 | 0.5938 |
| 0.8716 | 12.0 | 240 | 1.2533 | 0.5437 |
| 0.8739 | 13.0 | 260 | 1.1740 | 0.5625 |
| 0.8903 | 14.0 | 280 | 1.2089 | 0.55 |
| 0.8424 | 15.0 | 300 | 1.2022 | 0.5625 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1