---
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: squarerun_earlystop
  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. -->

# squarerun_earlystop

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2750
- F1 Macro: 0.4568
- F1 Micro: 0.5455
- F1 Weighted: 0.5111
- Precision Macro: 0.4686
- Precision Micro: 0.5455
- Precision Weighted: 0.5173
- Recall Macro: 0.4845
- Recall Micro: 0.5455
- Recall Weighted: 0.5455
- Accuracy: 0.5455

## 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: 40

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.9437        | 1.0   | 29   | 1.8987          | 0.1485   | 0.2576   | 0.1680      | 0.1192          | 0.2576          | 0.1321             | 0.2207       | 0.2576       | 0.2576          | 0.2576   |
| 1.4616        | 2.0   | 58   | 1.5844          | 0.3569   | 0.4242   | 0.4076      | 0.4336          | 0.4242          | 0.4738             | 0.3657       | 0.4242       | 0.4242          | 0.4242   |
| 1.9935        | 3.0   | 87   | 1.4952          | 0.3059   | 0.4242   | 0.3585      | 0.3795          | 0.4242          | 0.4097             | 0.3387       | 0.4242       | 0.4242          | 0.4242   |
| 1.3601        | 4.0   | 116  | 1.4319          | 0.3275   | 0.4167   | 0.3720      | 0.3223          | 0.4167          | 0.3618             | 0.3614       | 0.4167       | 0.4167          | 0.4167   |
| 1.1685        | 5.0   | 145  | 1.1508          | 0.4913   | 0.5833   | 0.5550      | 0.4887          | 0.5833          | 0.5484             | 0.5139       | 0.5833       | 0.5833          | 0.5833   |
| 1.2228        | 6.0   | 174  | 1.2663          | 0.4865   | 0.5076   | 0.5046      | 0.5339          | 0.5076          | 0.5644             | 0.4964       | 0.5076       | 0.5076          | 0.5076   |
| 1.2811        | 7.0   | 203  | 1.4596          | 0.4084   | 0.5303   | 0.4752      | 0.5582          | 0.5303          | 0.6068             | 0.4383       | 0.5303       | 0.5303          | 0.5303   |
| 1.7256        | 8.0   | 232  | 1.4908          | 0.4805   | 0.5682   | 0.5435      | 0.5333          | 0.5682          | 0.6122             | 0.5219       | 0.5682       | 0.5682          | 0.5682   |
| 0.4549        | 9.0   | 261  | 1.2969          | 0.5270   | 0.6136   | 0.5648      | 0.6664          | 0.6136          | 0.6757             | 0.5526       | 0.6136       | 0.6136          | 0.6136   |
| 0.5877        | 10.0  | 290  | 1.3581          | 0.4638   | 0.5758   | 0.5271      | 0.5632          | 0.5758          | 0.6293             | 0.5095       | 0.5758       | 0.5758          | 0.5758   |
| 0.3451        | 11.0  | 319  | 1.2491          | 0.5613   | 0.6136   | 0.6066      | 0.5909          | 0.6136          | 0.6111             | 0.5589       | 0.6136       | 0.6136          | 0.6136   |
| 0.4885        | 12.0  | 348  | 1.6862          | 0.5381   | 0.6288   | 0.6087      | 0.5515          | 0.6288          | 0.6225             | 0.5576       | 0.6288       | 0.6288          | 0.6288   |
| 0.3835        | 13.0  | 377  | 1.8354          | 0.5318   | 0.5379   | 0.5440      | 0.6396          | 0.5379          | 0.6577             | 0.5264       | 0.5379       | 0.5379          | 0.5379   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0