---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emo-vit-base-patch16-224-in21k
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6
---

<!-- 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. -->

# emo-vit-base-patch16-224-in21k

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1350
- Accuracy: 0.6

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 250

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0786        | 1.0   | 10   | 2.0448          | 0.2875   |
| 2.0107        | 2.0   | 20   | 1.9673          | 0.3125   |
| 1.8902        | 3.0   | 30   | 1.8561          | 0.4125   |
| 1.7355        | 4.0   | 40   | 1.6772          | 0.475    |
| 1.5861        | 5.0   | 50   | 1.5472          | 0.5      |
| 1.4665        | 6.0   | 60   | 1.4588          | 0.5375   |
| 1.3571        | 7.0   | 70   | 1.3812          | 0.5188   |
| 1.2465        | 8.0   | 80   | 1.3115          | 0.5312   |
| 1.1512        | 9.0   | 90   | 1.2910          | 0.525    |
| 1.0691        | 10.0  | 100  | 1.2342          | 0.5125   |
| 0.9837        | 11.0  | 110  | 1.2130          | 0.5437   |
| 0.9008        | 12.0  | 120  | 1.2073          | 0.5563   |
| 0.8315        | 13.0  | 130  | 1.1994          | 0.55     |
| 0.7634        | 14.0  | 140  | 1.1707          | 0.5563   |
| 0.709         | 15.0  | 150  | 1.1815          | 0.5563   |
| 0.6516        | 16.0  | 160  | 1.1622          | 0.5938   |
| 0.5933        | 17.0  | 170  | 1.2124          | 0.5312   |
| 0.5902        | 18.0  | 180  | 1.1782          | 0.5625   |
| 0.5122        | 19.0  | 190  | 1.2203          | 0.5625   |
| 0.4661        | 20.0  | 200  | 1.1928          | 0.5563   |
| 0.4797        | 21.0  | 210  | 1.1350          | 0.6      |
| 0.4459        | 22.0  | 220  | 1.2052          | 0.5563   |
| 0.4308        | 23.0  | 230  | 1.1729          | 0.5875   |
| 0.4121        | 24.0  | 240  | 1.2045          | 0.5375   |
| 0.3571        | 25.0  | 250  | 1.1906          | 0.6      |
| 0.3294        | 26.0  | 260  | 1.2311          | 0.5563   |
| 0.3661        | 27.0  | 270  | 1.2366          | 0.5375   |
| 0.328         | 28.0  | 280  | 1.2087          | 0.6      |
| 0.3352        | 29.0  | 290  | 1.2005          | 0.575    |
| 0.2923        | 30.0  | 300  | 1.2005          | 0.5813   |
| 0.2607        | 31.0  | 310  | 1.2309          | 0.5563   |
| 0.277         | 32.0  | 320  | 1.2385          | 0.5813   |
| 0.2678        | 33.0  | 330  | 1.2511          | 0.5563   |
| 0.2611        | 34.0  | 340  | 1.2675          | 0.575    |
| 0.2559        | 35.0  | 350  | 1.2869          | 0.575    |
| 0.2813        | 36.0  | 360  | 1.3965          | 0.55     |
| 0.2527        | 37.0  | 370  | 1.2851          | 0.6      |
| 0.2466        | 38.0  | 380  | 1.3265          | 0.55     |
| 0.2648        | 39.0  | 390  | 1.3024          | 0.575    |
| 0.2607        | 40.0  | 400  | 1.3884          | 0.5375   |
| 0.222         | 41.0  | 410  | 1.2922          | 0.5625   |
| 0.2095        | 42.0  | 420  | 1.3410          | 0.5437   |
| 0.197         | 43.0  | 430  | 1.3482          | 0.575    |
| 0.1964        | 44.0  | 440  | 1.3416          | 0.5687   |
| 0.2133        | 45.0  | 450  | 1.4440          | 0.5687   |
| 0.2095        | 46.0  | 460  | 1.3465          | 0.5437   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3