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---
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_ViT2TinyViT
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. -->
# KDRSSC_ViT2TinyViT
This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4414
- Accuracy: 0.9381
- Precision: 0.9385
- Recall: 0.9385
- F1: 0.9382
## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9089 | 1.0 | 148 | 0.5624 | 0.906 | 0.9072 | 0.9014 | 0.8987 |
| 0.4816 | 2.0 | 296 | 0.4759 | 0.94 | 0.9411 | 0.9389 | 0.9382 |
| 0.3958 | 3.0 | 444 | 0.4354 | 0.952 | 0.9503 | 0.9510 | 0.9496 |
| 0.3574 | 4.0 | 592 | 0.4273 | 0.949 | 0.9475 | 0.9470 | 0.9460 |
| 0.3406 | 5.0 | 740 | 0.4132 | 0.955 | 0.9548 | 0.9522 | 0.9523 |
| 0.3341 | 6.0 | 888 | 0.4164 | 0.951 | 0.9481 | 0.9503 | 0.9477 |
| 0.3314 | 7.0 | 1036 | 0.4087 | 0.957 | 0.9545 | 0.9538 | 0.9530 |
| 0.3302 | 8.0 | 1184 | 0.4075 | 0.955 | 0.9528 | 0.9517 | 0.9512 |
| 0.3295 | 9.0 | 1332 | 0.4067 | 0.956 | 0.9533 | 0.9533 | 0.9522 |
| 0.3292 | 10.0 | 1480 | 0.4071 | 0.956 | 0.9534 | 0.9533 | 0.9522 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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