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# 378A1_results

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: 0.4492
- Accuracy: 0.9014

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2401        | 1.0   | 37   | 1.0427          | 0.6582   |
| 0.669         | 2.0   | 74   | 0.5486          | 0.8418   |
| 0.4662        | 3.0   | 111  | 0.4012          | 0.8690   |
| 0.3211        | 4.0   | 148  | 0.5338          | 0.7942   |
| 0.2136        | 5.0   | 185  | 0.3189          | 0.8861   |
| 0.1626        | 6.0   | 222  | 0.4406          | 0.8435   |
| 0.1042        | 7.0   | 259  | 0.3812          | 0.8741   |
| 0.0688        | 8.0   | 296  | 0.3501          | 0.8946   |
| 0.0425        | 9.0   | 333  | 0.3845          | 0.8912   |
| 0.0586        | 10.0  | 370  | 0.3640          | 0.8980   |
| 0.0276        | 11.0  | 407  | 0.3708          | 0.9031   |
| 0.0342        | 12.0  | 444  | 0.3862          | 0.9082   |
| 0.0251        | 13.0  | 481  | 0.5206          | 0.8776   |
| 0.0209        | 14.0  | 518  | 0.4078          | 0.8929   |
| 0.0173        | 15.0  | 555  | 0.4168          | 0.8895   |
| 0.0159        | 16.0  | 592  | 0.4108          | 0.8997   |
| 0.0151        | 17.0  | 629  | 0.4176          | 0.9014   |
| 0.014         | 18.0  | 666  | 0.4228          | 0.9014   |
| 0.0131        | 19.0  | 703  | 0.4266          | 0.9014   |
| 0.0125        | 20.0  | 740  | 0.4301          | 0.9014   |
| 0.012         | 21.0  | 777  | 0.4339          | 0.9014   |
| 0.0115        | 22.0  | 814  | 0.4372          | 0.9014   |
| 0.0111        | 23.0  | 851  | 0.4401          | 0.9014   |
| 0.0107        | 24.0  | 888  | 0.4424          | 0.9014   |
| 0.0101        | 25.0  | 925  | 0.4444          | 0.9014   |
| 0.01          | 26.0  | 962  | 0.4461          | 0.9014   |
| 0.01          | 27.0  | 999  | 0.4475          | 0.9014   |
| 0.0099        | 28.0  | 1036 | 0.4485          | 0.9014   |
| 0.0097        | 29.0  | 1073 | 0.4490          | 0.9014   |
| 0.0097        | 30.0  | 1110 | 0.4492          | 0.9014   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3

label_0 label_1 label_2 label_3