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---
library_name: transformers
license: apache-2.0
base_model: dennisjooo/emotion_classification
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_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: 0.6375
---

<!-- 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_classification

This model is a fine-tuned version of [dennisjooo/emotion_classification](https://huggingface.co/dennisjooo/emotion_classification) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0965
- Accuracy: 0.6375

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1559        | 1.0   | 20   | 1.2425          | 0.5437   |
| 1.1243        | 2.0   | 40   | 1.1168          | 0.6312   |
| 1.0982        | 3.0   | 60   | 1.1411          | 0.6312   |
| 1.1412        | 4.0   | 80   | 1.1407          | 0.6625   |
| 1.1165        | 5.0   | 100  | 1.1910          | 0.6188   |
| 1.0722        | 6.0   | 120  | 1.1595          | 0.6125   |
| 1.1606        | 7.0   | 140  | 1.1311          | 0.6562   |
| 1.0792        | 8.0   | 160  | 1.1579          | 0.5938   |
| 1.0923        | 9.0   | 180  | 1.2815          | 0.5563   |
| 1.1298        | 10.0  | 200  | 1.0916          | 0.675    |


### Framework versions

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