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---
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-U8-40b
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: 0.8823529411764706
---
<!-- 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-U8-40b
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: 0.5666
- Accuracy: 0.8824
## 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: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3457 | 1.0 | 20 | 1.3070 | 0.4706 |
| 1.1498 | 2.0 | 40 | 1.0956 | 0.5686 |
| 0.8293 | 3.0 | 60 | 0.8270 | 0.6471 |
| 0.5448 | 4.0 | 80 | 0.6145 | 0.8235 |
| 0.3525 | 5.0 | 100 | 0.6439 | 0.7451 |
| 0.2436 | 6.0 | 120 | 0.5427 | 0.8235 |
| 0.195 | 7.0 | 140 | 0.6276 | 0.7843 |
| 0.1629 | 8.0 | 160 | 0.7868 | 0.7255 |
| 0.1697 | 9.0 | 180 | 0.8245 | 0.7255 |
| 0.1324 | 10.0 | 200 | 0.6599 | 0.8235 |
| 0.1714 | 11.0 | 220 | 0.7453 | 0.7647 |
| 0.0908 | 12.0 | 240 | 0.5666 | 0.8824 |
| 0.0812 | 13.0 | 260 | 0.9997 | 0.7451 |
| 0.0672 | 14.0 | 280 | 0.8049 | 0.8039 |
| 0.0843 | 15.0 | 300 | 0.6723 | 0.8431 |
| 0.0946 | 16.0 | 320 | 0.8892 | 0.7451 |
| 0.0684 | 17.0 | 340 | 1.1429 | 0.7451 |
| 0.0711 | 18.0 | 360 | 1.1384 | 0.7451 |
| 0.0677 | 19.0 | 380 | 1.0296 | 0.7843 |
| 0.0562 | 20.0 | 400 | 0.9803 | 0.7647 |
| 0.0688 | 21.0 | 420 | 0.9401 | 0.7843 |
| 0.0576 | 22.0 | 440 | 1.0823 | 0.7843 |
| 0.0892 | 23.0 | 460 | 1.0819 | 0.7255 |
| 0.063 | 24.0 | 480 | 1.0756 | 0.7647 |
| 0.055 | 25.0 | 500 | 0.9693 | 0.7647 |
| 0.0407 | 26.0 | 520 | 1.0132 | 0.7451 |
| 0.0562 | 27.0 | 540 | 1.0267 | 0.7843 |
| 0.0365 | 28.0 | 560 | 1.0530 | 0.7451 |
| 0.0363 | 29.0 | 580 | 0.9277 | 0.7843 |
| 0.0392 | 30.0 | 600 | 0.9798 | 0.8039 |
| 0.0374 | 31.0 | 620 | 1.0239 | 0.8039 |
| 0.0386 | 32.0 | 640 | 1.0221 | 0.8039 |
| 0.0345 | 33.0 | 660 | 1.0239 | 0.7843 |
| 0.035 | 34.0 | 680 | 1.0163 | 0.8039 |
| 0.0367 | 35.0 | 700 | 1.0902 | 0.8039 |
| 0.0219 | 36.0 | 720 | 1.1079 | 0.7843 |
| 0.0263 | 37.0 | 740 | 1.0727 | 0.8039 |
| 0.0261 | 38.0 | 760 | 1.0471 | 0.8039 |
| 0.0193 | 39.0 | 780 | 1.0347 | 0.8039 |
| 0.0301 | 40.0 | 800 | 1.0319 | 0.8039 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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