---
library_name: transformers
license: apache-2.0
base_model: dima806/facial_emotions_image_detection
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification2
  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: 0.66875
---

<!-- 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. -->

# image_classification2

This model is a fine-tuned version of [dima806/facial_emotions_image_detection](https://huggingface.co./dima806/facial_emotions_image_detection) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9519
- Accuracy: 0.6687

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8187        | 1.0   | 80   | 1.7527          | 0.4813   |
| 1.52          | 2.0   | 160  | 1.3596          | 0.6312   |
| 1.4072        | 3.0   | 240  | 1.2119          | 0.5875   |
| 1.0868        | 4.0   | 320  | 1.0981          | 0.625    |
| 0.9286        | 5.0   | 400  | 1.0133          | 0.6625   |
| 0.9353        | 6.0   | 480  | 0.9711          | 0.625    |
| 0.7437        | 7.0   | 560  | 0.9389          | 0.6562   |
| 0.6774        | 8.0   | 640  | 0.9519          | 0.6687   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1