---
license: apache-2.0
base_model: raffel-22/emotion_classification_2
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_classification_2_continue
  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: 0.725
---

<!-- 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_2_continue

This model is a fine-tuned version of [raffel-22/emotion_classification_2](https://huggingface.co/raffel-22/emotion_classification_2) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8978
- Accuracy: 0.725

## 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: 4e-05
- 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
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 20   | 0.9714          | 0.7063   |
| No log        | 2.0   | 40   | 0.9432          | 0.7188   |
| No log        | 3.0   | 60   | 0.9633          | 0.7      |
| No log        | 4.0   | 80   | 0.9322          | 0.7375   |
| No log        | 5.0   | 100  | 0.8530          | 0.7063   |
| No log        | 6.0   | 120  | 0.9063          | 0.7063   |
| No log        | 7.0   | 140  | 0.8451          | 0.7125   |
| No log        | 8.0   | 160  | 0.9672          | 0.6375   |
| No log        | 9.0   | 180  | 0.9036          | 0.6937   |
| No log        | 10.0  | 200  | 0.9261          | 0.6562   |
| No log        | 11.0  | 220  | 0.8963          | 0.6937   |
| No log        | 12.0  | 240  | 0.8852          | 0.7188   |
| No log        | 13.0  | 260  | 0.8728          | 0.7063   |
| No log        | 14.0  | 280  | 0.9559          | 0.6875   |
| No log        | 15.0  | 300  | 0.9352          | 0.65     |
| No log        | 16.0  | 320  | 0.8638          | 0.7      |
| No log        | 17.0  | 340  | 0.9156          | 0.7      |
| No log        | 18.0  | 360  | 1.0299          | 0.6687   |
| No log        | 19.0  | 380  | 0.8983          | 0.675    |
| No log        | 20.0  | 400  | 0.8858          | 0.7063   |
| No log        | 21.0  | 420  | 0.9699          | 0.6937   |
| No log        | 22.0  | 440  | 1.0603          | 0.625    |
| No log        | 23.0  | 460  | 1.0404          | 0.6312   |
| No log        | 24.0  | 480  | 0.8838          | 0.6937   |
| 0.4269        | 25.0  | 500  | 0.9280          | 0.6937   |
| 0.4269        | 26.0  | 520  | 0.9456          | 0.6937   |
| 0.4269        | 27.0  | 540  | 0.9640          | 0.6937   |
| 0.4269        | 28.0  | 560  | 0.9865          | 0.6937   |
| 0.4269        | 29.0  | 580  | 0.8900          | 0.7188   |
| 0.4269        | 30.0  | 600  | 0.9408          | 0.7063   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3