---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: NabeelShar/emotions_classifier
  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. -->

# NabeelShar/emotions_classifier

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: 1.1146
- Validation Loss: 1.6637
- Train Accuracy: 0.3625
- Epoch: 49

## 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': 0.0003, 'decay_steps': 32000, '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 | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.0910     | 2.0947          | 0.1062         | 0     |
| 2.0049     | 1.9103          | 0.2062         | 1     |
| 2.0473     | 1.9654          | 0.175          | 2     |
| 1.9824     | 2.1773          | 0.125          | 3     |
| 2.0538     | 2.0144          | 0.1875         | 4     |
| 1.9921     | 2.0826          | 0.1437         | 5     |
| 2.0904     | 2.0995          | 0.1812         | 6     |
| 2.0866     | 2.0908          | 0.1313         | 7     |
| 2.0718     | 2.0800          | 0.125          | 8     |
| 2.0511     | 2.0358          | 0.1938         | 9     |
| 1.9794     | 1.9049          | 0.2313         | 10    |
| 1.9289     | 1.8717          | 0.1875         | 11    |
| 1.8696     | 1.8451          | 0.2062         | 12    |
| 1.8361     | 1.8010          | 0.2062         | 13    |
| 1.8122     | 1.7457          | 0.225          | 14    |
| 1.7571     | 1.7331          | 0.25           | 15    |
| 1.6846     | 1.8783          | 0.25           | 16    |
| 1.6954     | 1.8015          | 0.25           | 17    |
| 1.7414     | 1.7329          | 0.1625         | 18    |
| 1.6662     | 1.6900          | 0.2625         | 19    |
| 1.6322     | 1.7607          | 0.25           | 20    |
| 1.5822     | 1.6670          | 0.3063         | 21    |
| 1.6279     | 1.6800          | 0.3            | 22    |
| 1.5737     | 1.7843          | 0.25           | 23    |
| 1.5851     | 1.6927          | 0.2875         | 24    |
| 1.4926     | 1.6640          | 0.2687         | 25    |
| 1.4879     | 1.7408          | 0.2812         | 26    |
| 1.5564     | 1.6668          | 0.275          | 27    |
| 1.5093     | 1.6259          | 0.3187         | 28    |
| 1.4428     | 1.6973          | 0.2437         | 29    |
| 1.4328     | 1.6412          | 0.2812         | 30    |
| 1.3778     | 1.6470          | 0.3187         | 31    |
| 1.4635     | 1.6411          | 0.325          | 32    |
| 1.4044     | 1.6643          | 0.2938         | 33    |
| 1.2991     | 1.6864          | 0.2875         | 34    |
| 1.3467     | 1.6124          | 0.2687         | 35    |
| 1.3422     | 1.6517          | 0.2687         | 36    |
| 1.3998     | 1.5634          | 0.325          | 37    |
| 1.2963     | 1.7403          | 0.3            | 38    |
| 1.3050     | 1.7550          | 0.3187         | 39    |
| 1.2988     | 1.6917          | 0.3438         | 40    |
| 1.2601     | 1.6739          | 0.3125         | 41    |
| 1.1943     | 1.7200          | 0.35           | 42    |
| 1.2663     | 1.6505          | 0.3312         | 43    |
| 1.2228     | 1.7337          | 0.3312         | 44    |
| 1.1413     | 1.7777          | 0.2812         | 45    |
| 1.1429     | 1.7138          | 0.3375         | 46    |
| 1.0760     | 1.7160          | 0.3187         | 47    |
| 1.1625     | 1.8049          | 0.3063         | 48    |
| 1.1146     | 1.6637          | 0.3625         | 49    |


### Framework versions

- Transformers 4.33.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3