---
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: '2024_08_13'
  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: 0.75
---

<!-- 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. -->

# 2024_08_13

This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6787
- Accuracy: 0.75

## 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: 1e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.7191        | 0.992   | 31   | 0.7459          | 0.25     |
| 0.6894        | 1.984   | 62   | 0.6787          | 0.75     |
| 0.5993        | 2.976   | 93   | 0.6090          | 0.75     |
| 0.5858        | 4.0     | 125  | 0.5702          | 0.75     |
| 0.5407        | 4.992   | 156  | 0.5572          | 0.75     |
| 0.6552        | 5.984   | 187  | 0.5553          | 0.75     |
| 0.5562        | 6.976   | 218  | 0.5529          | 0.75     |
| 0.6054        | 8.0     | 250  | 0.5519          | 0.75     |
| 0.7563        | 8.992   | 281  | 0.5518          | 0.75     |
| 0.5174        | 9.984   | 312  | 0.5523          | 0.75     |
| 0.3765        | 10.9760 | 343  | 0.5514          | 0.75     |
| 0.5727        | 12.0    | 375  | 0.5507          | 0.75     |
| 0.5613        | 12.992  | 406  | 0.5510          | 0.75     |
| 0.568         | 13.984  | 437  | 0.5510          | 0.75     |
| 0.6655        | 14.9760 | 468  | 0.5514          | 0.75     |
| 0.4883        | 16.0    | 500  | 0.5522          | 0.75     |
| 0.5317        | 16.992  | 531  | 0.5518          | 0.75     |
| 0.4501        | 17.984  | 562  | 0.5520          | 0.75     |
| 0.4616        | 18.976  | 593  | 0.5519          | 0.75     |
| 0.4522        | 20.0    | 625  | 0.5510          | 0.75     |
| 0.6326        | 20.992  | 656  | 0.5507          | 0.75     |
| 0.3828        | 21.984  | 687  | 0.5508          | 0.75     |
| 0.4283        | 22.976  | 718  | 0.5509          | 0.75     |
| 0.6701        | 24.0    | 750  | 0.5506          | 0.75     |
| 0.6157        | 24.992  | 781  | 0.5503          | 0.75     |
| 0.5657        | 25.984  | 812  | 0.5503          | 0.75     |
| 0.5127        | 26.976  | 843  | 0.5503          | 0.75     |
| 0.6178        | 28.0    | 875  | 0.5503          | 0.75     |
| 0.5679        | 28.992  | 906  | 0.5502          | 0.75     |
| 0.6102        | 29.76   | 930  | 0.5502          | 0.75     |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1