transformers safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:google/vit-base-patch16-224-in21k license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_classifier
  results:
  - task:
      name: Emotion Classifier
      type: emotion-classifier
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5520833333333334
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# emotion_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 the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2783
- Accuracy: 0.5521

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 35   | 2.0697          | 0.2014   |
| No log        | 2.0   | 70   | 2.0539          | 0.1875   |
| No log        | 3.0   | 105  | 2.0278          | 0.2014   |
| No log        | 4.0   | 140  | 1.9869          | 0.2639   |
| No log        | 5.0   | 175  | 1.9248          | 0.2986   |
| No log        | 6.0   | 210  | 1.8172          | 0.3403   |
| No log        | 7.0   | 245  | 1.7661          | 0.375    |
| No log        | 8.0   | 280  | 1.6933          | 0.4306   |
| No log        | 9.0   | 315  | 1.6493          | 0.4514   |
| No log        | 10.0  | 350  | 1.6028          | 0.4514   |
| No log        | 11.0  | 385  | 1.5580          | 0.4444   |
| No log        | 12.0  | 420  | 1.5267          | 0.5      |
| No log        | 13.0  | 455  | 1.4934          | 0.4861   |
| No log        | 14.0  | 490  | 1.4605          | 0.5208   |
| 1.6139        | 15.0  | 525  | 1.4499          | 0.5278   |
| 1.6139        | 16.0  | 560  | 1.4228          | 0.5347   |
| 1.6139        | 17.0  | 595  | 1.4109          | 0.5208   |
| 1.6139        | 18.0  | 630  | 1.3872          | 0.5139   |
| 1.6139        | 19.0  | 665  | 1.3640          | 0.5556   |
| 1.6139        | 20.0  | 700  | 1.3787          | 0.5208   |
| 1.6139        | 21.0  | 735  | 1.3820          | 0.5278   |
| 1.6139        | 22.0  | 770  | 1.3649          | 0.5069   |
| 1.6139        | 23.0  | 805  | 1.3508          | 0.5347   |
| 1.6139        | 24.0  | 840  | 1.3322          | 0.5417   |
| 1.6139        | 25.0  | 875  | 1.3577          | 0.5347   |
| 1.6139        | 26.0  | 910  | 1.3337          | 0.5625   |
| 1.6139        | 27.0  | 945  | 1.3578          | 0.5139   |
| 1.6139        | 28.0  | 980  | 1.3256          | 0.5556   |
| 0.8303        | 29.0  | 1015 | 1.3139          | 0.5833   |
| 0.8303        | 30.0  | 1050 | 1.3575          | 0.5139   |
| 0.8303        | 31.0  | 1085 | 1.3214          | 0.5625   |
| 0.8303        | 32.0  | 1120 | 1.3185          | 0.5486   |
| 0.8303        | 33.0  | 1155 | 1.3285          | 0.5417   |
| 0.8303        | 34.0  | 1190 | 1.3259          | 0.5903   |
| 0.8303        | 35.0  | 1225 | 1.3492          | 0.5556   |
| 0.8303        | 36.0  | 1260 | 1.3164          | 0.5764   |
| 0.8303        | 37.0  | 1295 | 1.3645          | 0.5417   |
| 0.8303        | 38.0  | 1330 | 1.3431          | 0.5347   |
| 0.8303        | 39.0  | 1365 | 1.3272          | 0.5278   |
| 0.8303        | 40.0  | 1400 | 1.3326          | 0.5972   |
| 0.8303        | 41.0  | 1435 | 1.3375          | 0.5486   |
| 0.8303        | 42.0  | 1470 | 1.3641          | 0.5556   |
| 0.3516        | 43.0  | 1505 | 1.3633          | 0.5278   |
| 0.3516        | 44.0  | 1540 | 1.3532          | 0.5278   |
| 0.3516        | 45.0  | 1575 | 1.3473          | 0.5903   |
| 0.3516        | 46.0  | 1610 | 1.3413          | 0.5833   |
| 0.3516        | 47.0  | 1645 | 1.4158          | 0.5556   |
| 0.3516        | 48.0  | 1680 | 1.3747          | 0.5903   |
| 0.3516        | 49.0  | 1715 | 1.4364          | 0.5347   |
| 0.3516        | 50.0  | 1750 | 1.4659          | 0.5417   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
