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---
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_boost9
  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_boost9

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: 1.2586
- Accuracy: 0.4151

## 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: 8
- 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
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3942        | 1.0   | 80   | 1.3566          | 0.3349   |
| 1.3192        | 2.0   | 160  | 1.3104          | 0.3585   |
| 1.2795        | 3.0   | 240  | 1.2999          | 0.3726   |
| 1.2419        | 4.0   | 320  | 1.2860          | 0.3726   |
| 1.2213        | 5.0   | 400  | 1.2894          | 0.3679   |
| 1.2287        | 6.0   | 480  | 1.2863          | 0.3632   |
| 1.2123        | 7.0   | 560  | 1.2879          | 0.3915   |
| 1.2124        | 8.0   | 640  | 1.2767          | 0.3868   |
| 1.2144        | 9.0   | 720  | 1.2851          | 0.3726   |
| 1.2202        | 10.0  | 800  | 1.2683          | 0.3962   |
| 1.1804        | 11.0  | 880  | 1.2659          | 0.4009   |
| 1.2031        | 12.0  | 960  | 1.2658          | 0.3962   |
| 1.1428        | 13.0  | 1040 | 1.2621          | 0.4057   |
| 1.1224        | 14.0  | 1120 | 1.2655          | 0.4104   |
| 1.1486        | 15.0  | 1200 | 1.2606          | 0.3962   |
| 1.1451        | 16.0  | 1280 | 1.2636          | 0.4057   |
| 1.1717        | 17.0  | 1360 | 1.2596          | 0.4057   |
| 1.1231        | 18.0  | 1440 | 1.2626          | 0.4057   |
| 1.1468        | 19.0  | 1520 | 1.2617          | 0.3962   |
| 1.0958        | 20.0  | 1600 | 1.2586          | 0.4151   |
| 1.1456        | 21.0  | 1680 | 1.2587          | 0.4104   |
| 1.127         | 22.0  | 1760 | 1.2590          | 0.4151   |
| 1.1308        | 23.0  | 1840 | 1.2586          | 0.4151   |
| 1.1433        | 24.0  | 1920 | 1.2585          | 0.4151   |
| 1.1492        | 25.0  | 2000 | 1.2585          | 0.4151   |


### Framework versions

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