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# msislam123/cifar10

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:
- Train Loss: 1.4844
- Train Accuracy: 0.5160
- Validation Loss: 1.8361
- Validation Accuracy: 0.3676
- Epoch: 19

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 59840, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.7038     | 0.1213         | 2.5039          | 0.1698              | 0     |
| 2.4263     | 0.1935         | 2.3429          | 0.2179              | 1     |
| 2.2970     | 0.2343         | 2.1942          | 0.2901              | 2     |
| 2.2132     | 0.2694         | 2.1083          | 0.3115              | 3     |
| 2.1136     | 0.2998         | 2.0528          | 0.3102              | 4     |
| 2.0533     | 0.3145         | 2.0046          | 0.3182              | 5     |
| 2.0016     | 0.3292         | 1.9495          | 0.3356              | 6     |
| 1.9511     | 0.3463         | 1.9589          | 0.3182              | 7     |
| 1.9106     | 0.3636         | 1.9360          | 0.3249              | 8     |
| 1.8807     | 0.3700         | 1.9207          | 0.3396              | 9     |
| 1.8368     | 0.3790         | 1.8890          | 0.3556              | 10    |
| 1.8118     | 0.3951         | 1.8834          | 0.3489              | 11    |
| 1.7714     | 0.3967         | 1.8410          | 0.3730              | 12    |
| 1.7185     | 0.4225         | 1.8576          | 0.3396              | 13    |
| 1.6796     | 0.4439         | 1.8087          | 0.3743              | 14    |
| 1.6593     | 0.4519         | 1.8192          | 0.3543              | 15    |
| 1.6208     | 0.4539         | 1.8129          | 0.3650              | 16    |
| 1.5826     | 0.4826         | 1.8316          | 0.3663              | 17    |
| 1.5399     | 0.4913         | 1.7991          | 0.3650              | 18    |
| 1.4844     | 0.5160         | 1.8361          | 0.3676              | 19    |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7 label_8 label_9 label_10 label_11 label_12 label_13 label_14 label_15 label_16