---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion-classification
  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: 0.51875
---

<!-- 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-classification

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: 1.3560
- Accuracy: 0.5188

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 1.6699          | 0.4313   |
| 1.5821        | 2.0   | 10   | 1.6118          | 0.4562   |
| 1.5821        | 3.0   | 15   | 1.5550          | 0.475    |
| 1.445         | 4.0   | 20   | 1.5128          | 0.5062   |
| 1.445         | 5.0   | 25   | 1.4508          | 0.5375   |
| 1.3202        | 6.0   | 30   | 1.4364          | 0.5      |
| 1.3202        | 7.0   | 35   | 1.3776          | 0.575    |
| 1.2242        | 8.0   | 40   | 1.3966          | 0.5      |
| 1.2242        | 9.0   | 45   | 1.3724          | 0.525    |
| 1.1589        | 10.0  | 50   | 1.3483          | 0.525    |
| 1.1589        | 11.0  | 55   | 1.3186          | 0.5687   |
| 1.0962        | 12.0  | 60   | 1.3295          | 0.5375   |
| 1.0962        | 13.0  | 65   | 1.3058          | 0.5875   |
| 1.0542        | 14.0  | 70   | 1.3296          | 0.5375   |
| 1.0542        | 15.0  | 75   | 1.3185          | 0.5813   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1