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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
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. -->
# results
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: 1.4656
- Accuracy: 0.8125
- F1: 0.8141
## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log | 1.0 | 17 | 0.8876 | 0.5865 | 0.5688 |
| No log | 2.0 | 34 | 0.8620 | 0.6090 | 0.6067 |
| No log | 3.0 | 51 | 0.7611 | 0.6842 | 0.6783 |
| No log | 4.0 | 68 | 0.6987 | 0.6842 | 0.6741 |
| No log | 5.0 | 85 | 0.6540 | 0.6917 | 0.6872 |
| No log | 6.0 | 102 | 0.7933 | 0.6767 | 0.6407 |
| No log | 7.0 | 119 | 0.4766 | 0.8195 | 0.8152 |
| No log | 8.0 | 136 | 0.4624 | 0.8271 | 0.8231 |
| No log | 9.0 | 153 | 0.4528 | 0.8271 | 0.8277 |
| No log | 10.0 | 170 | 0.4641 | 0.8120 | 0.8087 |
| No log | 11.0 | 187 | 0.6063 | 0.7368 | 0.7231 |
| No log | 12.0 | 204 | 0.4783 | 0.7594 | 0.7596 |
| No log | 13.0 | 221 | 0.4987 | 0.7970 | 0.7990 |
| No log | 14.0 | 238 | 0.6023 | 0.7669 | 0.7603 |
| No log | 15.0 | 255 | 0.4588 | 0.8271 | 0.8254 |
| No log | 16.0 | 272 | 0.4362 | 0.8120 | 0.8130 |
| No log | 17.0 | 289 | 0.5342 | 0.8271 | 0.8280 |
| No log | 18.0 | 306 | 0.5012 | 0.8120 | 0.8124 |
| No log | 19.0 | 323 | 0.4891 | 0.8496 | 0.8498 |
| No log | 20.0 | 340 | 0.8525 | 0.7744 | 0.7714 |
| No log | 21.0 | 357 | 0.5291 | 0.8195 | 0.8209 |
| No log | 22.0 | 374 | 0.5355 | 0.8271 | 0.8264 |
| No log | 23.0 | 391 | 0.6323 | 0.8045 | 0.8041 |
| No log | 24.0 | 408 | 0.6973 | 0.8346 | 0.8334 |
| No log | 25.0 | 425 | 0.6705 | 0.8571 | 0.8569 |
| No log | 26.0 | 442 | 0.6056 | 0.8571 | 0.8572 |
| No log | 27.0 | 459 | 0.7864 | 0.8421 | 0.8421 |
| No log | 28.0 | 476 | 0.7067 | 0.8346 | 0.8351 |
| No log | 29.0 | 493 | 0.6695 | 0.8571 | 0.8567 |
| 0.3504 | 30.0 | 510 | 0.6680 | 0.8647 | 0.8646 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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