|
---
|
|
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-ve-U11-b-24
|
|
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: 0.9130434782608695
|
|
---
|
|
|
|
<!-- 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-ve-U11-b-24
|
|
|
|
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: 0.4436
|
|
- Accuracy: 0.9130
|
|
|
|
## 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: 24
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| No log | 0.92 | 6 | 1.3798 | 0.5435 |
|
|
| 1.3792 | 2.0 | 13 | 1.3091 | 0.6522 |
|
|
| 1.3792 | 2.92 | 19 | 1.2227 | 0.5870 |
|
|
| 1.2783 | 4.0 | 26 | 1.1263 | 0.6087 |
|
|
| 1.1226 | 4.92 | 32 | 1.0466 | 0.6522 |
|
|
| 1.1226 | 6.0 | 39 | 0.9854 | 0.5870 |
|
|
| 0.9881 | 6.92 | 45 | 0.9303 | 0.6957 |
|
|
| 0.8707 | 8.0 | 52 | 0.8806 | 0.7826 |
|
|
| 0.8707 | 8.92 | 58 | 0.8234 | 0.7826 |
|
|
| 0.7604 | 10.0 | 65 | 0.7159 | 0.8261 |
|
|
| 0.6452 | 10.92 | 71 | 0.6929 | 0.8478 |
|
|
| 0.6452 | 12.0 | 78 | 0.6491 | 0.8696 |
|
|
| 0.5576 | 12.92 | 84 | 0.5924 | 0.8478 |
|
|
| 0.4708 | 14.0 | 91 | 0.5551 | 0.8478 |
|
|
| 0.4708 | 14.92 | 97 | 0.6354 | 0.8043 |
|
|
| 0.422 | 16.0 | 104 | 0.5130 | 0.8696 |
|
|
| 0.3546 | 16.92 | 110 | 0.5302 | 0.8696 |
|
|
| 0.3546 | 18.0 | 117 | 0.4436 | 0.9130 |
|
|
| 0.3353 | 18.92 | 123 | 0.5621 | 0.8261 |
|
|
| 0.3106 | 20.0 | 130 | 0.4912 | 0.8696 |
|
|
| 0.3106 | 20.92 | 136 | 0.4747 | 0.8913 |
|
|
| 0.312 | 22.0 | 143 | 0.4603 | 0.8913 |
|
|
| 0.312 | 22.15 | 144 | 0.4598 | 0.8913 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.36.2
|
|
- Pytorch 2.1.2+cu118
|
|
- Datasets 2.16.1
|
|
- Tokenizers 0.15.0
|
|
|
