---
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: 0.875
---

<!-- 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 was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8208
- Accuracy: 0.875

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cf23277c497672354225cd/jrX1Xnbrww6EFXh8fo8tI.png)

KeyboardInterrupt: because full disk, continue from checkpoint 270 / from epoch 54
checkpoint = "C:\Users\willi\Documents\MachineLearning_Collab\model\emotion-classification\checkpoint-270"


![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cf23277c497672354225cd/EeFYcfAfjX07fCuJWBWZo.png)

| Training Loss | Epoch |  Validation Loss | Accuracy |
|:-------------:|:-----:|:----------------:|:--------:|
| 0.8456        |  55   |     0.8537       | 0.8562   |
| 0.7982        |  56   |     0.8021       | 0.8875   |
| 0.8028        |  57   |     0.8028       | 0.8438   |

The result of evaluation from trainer.evaluate(eval_dataset=emotion["test"]): 

{'eval_loss': 0.8208037614822388, 'eval_accuracy': 0.875, 'eval_runtime': 5.3137, 'eval_samples_per_second': 30.111, 'eval_steps_per_second': 0.941, 'epoch': 3.0}

### Framework versions

- Transformers 4.41.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1