|
---
|
|
license: apache-2.0
|
|
base_model: google/vit-base-patch16-224
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagefolder
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: vit-base-patch16-224-RU2-10
|
|
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: 0.8166666666666667
|
|
---
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
# vit-base-patch16-224-RU2-10
|
|
|
|
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.6802
|
|
- Accuracy: 0.8167
|
|
|
|
## 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: 5.5e-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: 0.05
|
|
- num_epochs: 10
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| 1.1641 | 0.99 | 38 | 0.9789 | 0.7333 |
|
|
| 0.5847 | 2.0 | 77 | 0.6371 | 0.8167 |
|
|
| 0.2844 | 2.99 | 115 | 0.6706 | 0.75 |
|
|
| 0.2275 | 4.0 | 154 | 0.5359 | 0.8167 |
|
|
| 0.1539 | 4.99 | 192 | 0.6067 | 0.8167 |
|
|
| 0.1113 | 6.0 | 231 | 0.7887 | 0.7667 |
|
|
| 0.1117 | 6.99 | 269 | 0.6443 | 0.8167 |
|
|
| 0.1088 | 8.0 | 308 | 0.6429 | 0.85 |
|
|
| 0.0824 | 8.99 | 346 | 0.6499 | 0.8333 |
|
|
| 0.0834 | 9.87 | 380 | 0.6802 | 0.8167 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.36.2
|
|
- Pytorch 2.1.2+cu118
|
|
- Datasets 2.16.1
|
|
- Tokenizers 0.15.0
|
|
|
