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---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: squarerun2
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. -->
# squarerun2
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4284
- F1 Macro: 0.4676
- F1 Micro: 0.5606
- F1 Weighted: 0.5361
- Precision Macro: 0.4718
- Precision Micro: 0.5606
- Precision Weighted: 0.5334
- Recall Macro: 0.4835
- Recall Micro: 0.5606
- Recall Weighted: 0.5606
- Accuracy: 0.5606
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.9016 | 1.0 | 29 | 1.8764 | 0.1011 | 0.2424 | 0.1401 | 0.0721 | 0.2424 | 0.1001 | 0.1761 | 0.2424 | 0.2424 | 0.2424 |
| 1.8787 | 2.0 | 58 | 1.8750 | 0.0485 | 0.2045 | 0.0695 | 0.0292 | 0.2045 | 0.0418 | 0.1429 | 0.2045 | 0.2045 | 0.2045 |
| 1.9345 | 3.0 | 87 | 1.8624 | 0.0485 | 0.2045 | 0.0695 | 0.0292 | 0.2045 | 0.0418 | 0.1429 | 0.2045 | 0.2045 | 0.2045 |
| 1.6663 | 4.0 | 116 | 1.7239 | 0.2230 | 0.3561 | 0.2738 | 0.3173 | 0.3561 | 0.3549 | 0.2725 | 0.3561 | 0.3561 | 0.3561 |
| 1.3847 | 5.0 | 145 | 1.4880 | 0.3420 | 0.4697 | 0.4038 | 0.4521 | 0.4697 | 0.4846 | 0.3893 | 0.4697 | 0.4697 | 0.4697 |
| 1.6559 | 6.0 | 174 | 1.4056 | 0.3479 | 0.4773 | 0.4108 | 0.3865 | 0.4773 | 0.4276 | 0.3870 | 0.4773 | 0.4773 | 0.4773 |
| 1.335 | 7.0 | 203 | 1.3768 | 0.3875 | 0.5152 | 0.4527 | 0.3933 | 0.5152 | 0.4447 | 0.4265 | 0.5152 | 0.5152 | 0.5152 |
| 1.2514 | 8.0 | 232 | 1.2345 | 0.4536 | 0.5606 | 0.5207 | 0.4701 | 0.5606 | 0.5257 | 0.4766 | 0.5606 | 0.5606 | 0.5606 |
| 0.6979 | 9.0 | 261 | 1.1501 | 0.5305 | 0.6364 | 0.6097 | 0.5491 | 0.6364 | 0.6127 | 0.5391 | 0.6364 | 0.6364 | 0.6364 |
| 1.0417 | 10.0 | 290 | 1.1654 | 0.5206 | 0.6136 | 0.5900 | 0.5215 | 0.6136 | 0.5935 | 0.5464 | 0.6136 | 0.6136 | 0.6136 |
| 0.7314 | 11.0 | 319 | 1.1566 | 0.5376 | 0.6212 | 0.6109 | 0.5387 | 0.6212 | 0.6154 | 0.5514 | 0.6212 | 0.6212 | 0.6212 |
| 0.7902 | 12.0 | 348 | 1.1624 | 0.5397 | 0.6212 | 0.6140 | 0.5422 | 0.6212 | 0.6209 | 0.5505 | 0.6212 | 0.6212 | 0.6212 |
| 0.7503 | 13.0 | 377 | 1.1359 | 0.5377 | 0.6288 | 0.6126 | 0.5472 | 0.6288 | 0.6143 | 0.5455 | 0.6288 | 0.6288 | 0.6288 |
| 0.586 | 14.0 | 406 | 1.1512 | 0.5441 | 0.6288 | 0.6141 | 0.5361 | 0.6288 | 0.6033 | 0.5557 | 0.6288 | 0.6288 | 0.6288 |
| 0.6869 | 15.0 | 435 | 1.1306 | 0.5323 | 0.6288 | 0.6117 | 0.5270 | 0.6288 | 0.6043 | 0.5475 | 0.6288 | 0.6288 | 0.6288 |
| 0.5498 | 16.0 | 464 | 1.1293 | 0.5373 | 0.6288 | 0.6117 | 0.5353 | 0.6288 | 0.6039 | 0.5471 | 0.6288 | 0.6288 | 0.6288 |
| 0.5037 | 17.0 | 493 | 1.1635 | 0.5290 | 0.6212 | 0.6005 | 0.5374 | 0.6212 | 0.6022 | 0.5398 | 0.6212 | 0.6212 | 0.6212 |
| 0.3624 | 18.0 | 522 | 1.0994 | 0.5700 | 0.6591 | 0.6414 | 0.5815 | 0.6591 | 0.6409 | 0.5743 | 0.6591 | 0.6591 | 0.6591 |
| 0.3387 | 19.0 | 551 | 1.0944 | 0.5643 | 0.6515 | 0.6367 | 0.5556 | 0.6515 | 0.6268 | 0.5781 | 0.6515 | 0.6515 | 0.6515 |
| 0.4052 | 20.0 | 580 | 1.0934 | 0.5683 | 0.6591 | 0.6432 | 0.5681 | 0.6591 | 0.6393 | 0.5798 | 0.6591 | 0.6591 | 0.6591 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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