---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-base-224-22k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Validated_Balanced_Raw_Data_model_boost7
  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_boost7

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the Logiroad/Validated_Balanced_Raw_Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1008
- 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: 1.5e-05
- train_batch_size: 16
- 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: 25.0
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.3316          | 0.3491   |
| 1.3694        | 2.0   | 80   | 1.2695          | 0.3726   |
| 1.291         | 3.0   | 120  | 1.2237          | 0.4151   |
| 1.2374        | 4.0   | 160  | 1.1886          | 0.4481   |
| 1.1815        | 5.0   | 200  | 1.1870          | 0.4387   |
| 1.1815        | 6.0   | 240  | 1.1726          | 0.4717   |
| 1.1479        | 7.0   | 280  | 1.1224          | 0.4858   |
| 1.0818        | 8.0   | 320  | 1.1309          | 0.4717   |
| 1.0507        | 9.0   | 360  | 1.1351          | 0.4811   |
| 1.0198        | 10.0  | 400  | 1.1314          | 0.5189   |
| 1.0198        | 11.0  | 440  | 1.1235          | 0.5047   |
| 1.0075        | 12.0  | 480  | 1.1136          | 0.5283   |
| 0.9692        | 13.0  | 520  | 1.1230          | 0.5094   |
| 0.919         | 14.0  | 560  | 1.1158          | 0.5      |
| 0.9306        | 15.0  | 600  | 1.1089          | 0.5236   |
| 0.9306        | 16.0  | 640  | 1.1008          | 0.5425   |
| 0.89          | 17.0  | 680  | 1.1071          | 0.5236   |
| 0.8853        | 18.0  | 720  | 1.1110          | 0.5236   |
| 0.8852        | 19.0  | 760  | 1.1026          | 0.5330   |
| 0.824         | 20.0  | 800  | 1.1056          | 0.5377   |
| 0.824         | 21.0  | 840  | 1.1088          | 0.5283   |
| 0.8327        | 22.0  | 880  | 1.1065          | 0.5283   |
| 0.832         | 23.0  | 920  | 1.1063          | 0.5330   |
| 0.8801        | 24.0  | 960  | 1.1065          | 0.5330   |
| 0.8372        | 25.0  | 1000 | 1.1065          | 0.5330   |


### Framework versions

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