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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Validated_Balanced_Raw_Data_model_vit
results: []
---
<!-- 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. -->
# Validated_Balanced_Raw_Data_model_vit
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the Logiroad/Validated_Balanced_Raw_Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2154
- Accuracy: 0.5094
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 25.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4452 | 1.0 | 80 | 1.4537 | 0.2406 |
| 1.3534 | 2.0 | 160 | 1.4004 | 0.3538 |
| 1.2977 | 3.0 | 240 | 1.3417 | 0.3774 |
| 1.2604 | 4.0 | 320 | 1.3132 | 0.3774 |
| 1.2428 | 5.0 | 400 | 1.2443 | 0.4009 |
| 1.213 | 6.0 | 480 | 1.2148 | 0.4198 |
| 1.1426 | 7.0 | 560 | 1.2096 | 0.4670 |
| 1.1657 | 8.0 | 640 | 1.2066 | 0.4670 |
| 1.1249 | 9.0 | 720 | 1.2209 | 0.4387 |
| 1.1622 | 10.0 | 800 | 1.1446 | 0.4811 |
| 1.0625 | 11.0 | 880 | 1.1742 | 0.4670 |
| 1.1157 | 12.0 | 960 | 1.2200 | 0.4434 |
| 1.0807 | 13.0 | 1040 | 1.2117 | 0.4670 |
| 1.0629 | 14.0 | 1120 | 1.2296 | 0.4811 |
| 1.0323 | 15.0 | 1200 | 1.1887 | 0.4906 |
| 1.0128 | 16.0 | 1280 | 1.2075 | 0.4953 |
| 1.0266 | 17.0 | 1360 | 1.2082 | 0.5 |
| 1.004 | 18.0 | 1440 | 1.2154 | 0.5094 |
| 0.9543 | 19.0 | 1520 | 1.2048 | 0.5047 |
| 0.9439 | 20.0 | 1600 | 1.2218 | 0.4906 |
| 0.9891 | 21.0 | 1680 | 1.2136 | 0.4906 |
| 0.9801 | 22.0 | 1760 | 1.2166 | 0.4858 |
| 0.9632 | 23.0 | 1840 | 1.2149 | 0.4906 |
| 0.9584 | 24.0 | 1920 | 1.2135 | 0.4906 |
| 0.9561 | 25.0 | 2000 | 1.2136 | 0.4906 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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