---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21K
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-cards-blackjack
  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. -->

# finetuned-cards-blackjack

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: 0.9121
- Accuracy: 0.7710

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1307        | 0.24  | 100  | 3.0180          | 0.2093   |
| 2.7372        | 0.48  | 200  | 2.5301          | 0.2762   |
| 2.4969        | 0.73  | 300  | 2.1760          | 0.3439   |
| 2.1973        | 0.97  | 400  | 2.0103          | 0.3756   |
| 1.8847        | 1.21  | 500  | 1.8402          | 0.4108   |
| 1.746         | 1.45  | 600  | 1.7051          | 0.4803   |
| 1.8698        | 1.69  | 700  | 1.5985          | 0.4889   |
| 1.7261        | 1.94  | 800  | 1.4312          | 0.5840   |
| 1.7385        | 2.18  | 900  | 1.3585          | 0.6286   |
| 1.5873        | 2.42  | 1000 | 1.2374          | 0.6758   |
| 1.4775        | 2.66  | 1100 | 1.1352          | 0.7024   |
| 1.2697        | 2.91  | 1200 | 1.1044          | 0.7093   |
| 1.2137        | 3.15  | 1300 | 1.0006          | 0.7616   |
| 1.423         | 3.39  | 1400 | 0.9589          | 0.7744   |
| 1.0098        | 3.63  | 1500 | 0.9360          | 0.7684   |
| 1.1325        | 3.87  | 1600 | 0.9121          | 0.7710   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2