---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-small-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Validated_Balanced_Raw_Data_model_boost8
  results: []
---

<!-- 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. -->

# Validated_Balanced_Raw_Data_model_boost8

This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the Logiroad/Validated_Balanced_Raw_Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1054
- Accuracy: 0.5425

## 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: 8
- eval_batch_size: 16
- seed: 1337
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 25
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.326         | 1.0   | 80   | 1.2990          | 0.3868   |
| 1.2698        | 2.0   | 160  | 1.2875          | 0.3726   |
| 1.2271        | 3.0   | 240  | 1.2136          | 0.4245   |
| 1.1742        | 4.0   | 320  | 1.1844          | 0.4717   |
| 1.1507        | 5.0   | 400  | 1.1472          | 0.4906   |
| 1.1228        | 6.0   | 480  | 1.1568          | 0.4623   |
| 1.0484        | 7.0   | 560  | 1.1222          | 0.4811   |
| 1.0224        | 8.0   | 640  | 1.1054          | 0.5425   |
| 0.9876        | 9.0   | 720  | 1.1333          | 0.5      |
| 0.9897        | 10.0  | 800  | 1.1368          | 0.4811   |
| 0.9133        | 11.0  | 880  | 1.0923          | 0.5      |
| 0.8814        | 12.0  | 960  | 1.1101          | 0.4717   |
| 0.8185        | 13.0  | 1040 | 1.1416          | 0.4953   |
| 0.7917        | 14.0  | 1120 | 1.1237          | 0.5047   |
| 0.7773        | 15.0  | 1200 | 1.0994          | 0.5047   |
| 0.7289        | 16.0  | 1280 | 1.1059          | 0.5094   |
| 0.7337        | 17.0  | 1360 | 1.1085          | 0.5142   |
| 0.7052        | 18.0  | 1440 | 1.1131          | 0.5189   |
| 0.6703        | 19.0  | 1520 | 1.1068          | 0.5330   |
| 0.6482        | 20.0  | 1600 | 1.1251          | 0.5189   |
| 0.6421        | 21.0  | 1680 | 1.1164          | 0.5283   |
| 0.6738        | 22.0  | 1760 | 1.1147          | 0.5377   |
| 0.6459        | 23.0  | 1840 | 1.1152          | 0.5283   |
| 0.6302        | 24.0  | 1920 | 1.1156          | 0.5283   |
| 0.689         | 25.0  | 2000 | 1.1157          | 0.5283   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3