---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_face_image_classification_v2
  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: 0.48125
---

<!-- 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. -->

# emotion_face_image_classification_v2

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: 1.5157
- Accuracy: 0.4813

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 150
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 2    | 2.0924          | 0.15     |
| No log        | 2.0   | 5    | 2.1024          | 0.0938   |
| No log        | 2.8   | 7    | 2.0935          | 0.1375   |
| No log        | 4.0   | 10   | 2.0893          | 0.15     |
| No log        | 4.8   | 12   | 2.0900          | 0.15     |
| No log        | 6.0   | 15   | 2.0987          | 0.0813   |
| No log        | 6.8   | 17   | 2.0901          | 0.1      |
| No log        | 8.0   | 20   | 2.0872          | 0.15     |
| No log        | 8.8   | 22   | 2.0831          | 0.1375   |
| No log        | 10.0  | 25   | 2.0750          | 0.1437   |
| No log        | 10.8  | 27   | 2.0744          | 0.175    |
| No log        | 12.0  | 30   | 2.0778          | 0.1437   |
| No log        | 12.8  | 32   | 2.0729          | 0.1812   |
| No log        | 14.0  | 35   | 2.0676          | 0.1625   |
| No log        | 14.8  | 37   | 2.0694          | 0.1688   |
| No log        | 16.0  | 40   | 2.0562          | 0.1625   |
| No log        | 16.8  | 42   | 2.0498          | 0.1938   |
| No log        | 18.0  | 45   | 2.0393          | 0.2188   |
| No log        | 18.8  | 47   | 2.0458          | 0.2062   |
| No log        | 20.0  | 50   | 2.0289          | 0.2125   |
| No log        | 20.8  | 52   | 2.0226          | 0.2437   |
| No log        | 22.0  | 55   | 1.9997          | 0.2625   |
| No log        | 22.8  | 57   | 1.9855          | 0.3187   |
| No log        | 24.0  | 60   | 1.9571          | 0.3187   |
| No log        | 24.8  | 62   | 1.9473          | 0.3375   |
| No log        | 26.0  | 65   | 1.9080          | 0.3187   |
| No log        | 26.8  | 67   | 1.8894          | 0.35     |
| No log        | 28.0  | 70   | 1.8407          | 0.375    |
| No log        | 28.8  | 72   | 1.8083          | 0.3438   |
| No log        | 30.0  | 75   | 1.7652          | 0.3563   |
| No log        | 30.8  | 77   | 1.7281          | 0.3563   |
| No log        | 32.0  | 80   | 1.6729          | 0.4062   |
| No log        | 32.8  | 82   | 1.6527          | 0.3937   |
| No log        | 34.0  | 85   | 1.6044          | 0.4562   |
| No log        | 34.8  | 87   | 1.5899          | 0.4313   |
| No log        | 36.0  | 90   | 1.5488          | 0.4313   |
| No log        | 36.8  | 92   | 1.5340          | 0.45     |
| No log        | 38.0  | 95   | 1.5227          | 0.4875   |
| No log        | 38.8  | 97   | 1.4846          | 0.4875   |
| No log        | 40.0  | 100  | 1.4579          | 0.4688   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3