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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mutli_class_clasification
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. -->
# mutli_class_clasification
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8333
- Accuracy: 0.8796
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4273 | 1.0 | 370 | 0.8333 | 0.8796 |
| 0.4584 | 2.0 | 740 | 0.4355 | 0.9161 |
| 0.354 | 3.0 | 1110 | 0.3483 | 0.9296 |
| 0.299 | 4.0 | 1480 | 0.3173 | 0.9330 |
| 0.2639 | 5.0 | 1850 | 0.3092 | 0.9310 |
### Framework versions
- Transformers 4.55.3
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.2
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