transformers tf vit image-classification generated_from_keras_callback base_model:google/vit-base-patch16-224-in21k license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: DownwardSpiral33/hands_palms_classifier_rot01
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# DownwardSpiral33/hands_palms_classifier_rot01

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: 0.2863
- Validation Loss: 0.7353
- Train Accuracy: 0.6452
- Epoch: 45

## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 17400, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.6965     | 0.6687          | 0.5806         | 0     |
| 0.6851     | 0.6601          | 0.6452         | 1     |
| 0.6753     | 0.6519          | 0.6452         | 2     |
| 0.6644     | 0.6471          | 0.6452         | 3     |
| 0.6548     | 0.6405          | 0.6129         | 4     |
| 0.6541     | 0.6340          | 0.6774         | 5     |
| 0.6436     | 0.6266          | 0.6774         | 6     |
| 0.6364     | 0.6223          | 0.6452         | 7     |
| 0.6206     | 0.6112          | 0.6774         | 8     |
| 0.6166     | 0.6024          | 0.6774         | 9     |
| 0.6150     | 0.5970          | 0.7097         | 10    |
| 0.6019     | 0.5863          | 0.7097         | 11    |
| 0.5895     | 0.5824          | 0.7097         | 12    |
| 0.5866     | 0.5862          | 0.7097         | 13    |
| 0.5813     | 0.5742          | 0.6774         | 14    |
| 0.5586     | 0.5683          | 0.7097         | 15    |
| 0.5519     | 0.5749          | 0.7419         | 16    |
| 0.5311     | 0.5906          | 0.6774         | 17    |
| 0.5440     | 0.5588          | 0.6774         | 18    |
| 0.5130     | 0.5439          | 0.7097         | 19    |
| 0.5104     | 0.5469          | 0.6452         | 20    |
| 0.4894     | 0.5574          | 0.6452         | 21    |
| 0.4903     | 0.5527          | 0.6129         | 22    |
| 0.4903     | 0.5366          | 0.6452         | 23    |
| 0.4875     | 0.5562          | 0.7097         | 24    |
| 0.4625     | 0.5090          | 0.7097         | 25    |
| 0.4532     | 0.5489          | 0.7097         | 26    |
| 0.4018     | 0.5594          | 0.7097         | 27    |
| 0.4600     | 0.6152          | 0.6774         | 28    |
| 0.4199     | 0.5669          | 0.6774         | 29    |
| 0.4406     | 0.6120          | 0.6774         | 30    |
| 0.3885     | 0.5903          | 0.6452         | 31    |
| 0.4071     | 0.6163          | 0.6452         | 32    |
| 0.4056     | 0.5257          | 0.7419         | 33    |
| 0.4037     | 0.5606          | 0.6774         | 34    |
| 0.3522     | 0.5646          | 0.6452         | 35    |
| 0.3358     | 0.6367          | 0.6774         | 36    |
| 0.3419     | 0.6752          | 0.6774         | 37    |
| 0.3567     | 0.5802          | 0.6452         | 38    |
| 0.3769     | 0.5885          | 0.7097         | 39    |
| 0.3332     | 0.5860          | 0.7097         | 40    |
| 0.3818     | 0.5612          | 0.7419         | 41    |
| 0.3463     | 0.5921          | 0.7097         | 42    |
| 0.3244     | 0.6015          | 0.7097         | 43    |
| 0.2958     | 0.6124          | 0.7097         | 44    |
| 0.2863     | 0.7353          | 0.6452         | 45    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0
