---
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_boost5
  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_boost5

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: 1.1317
- Accuracy: 0.5377

## 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: 2e-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: 0.1
- num_epochs: 30.0
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3971        | 1.0   | 80   | 1.3381          | 0.3585   |
| 1.3299        | 2.0   | 160  | 1.2897          | 0.3632   |
| 1.2782        | 3.0   | 240  | 1.2422          | 0.4151   |
| 1.2159        | 4.0   | 320  | 1.1955          | 0.4434   |
| 1.1707        | 5.0   | 400  | 1.1769          | 0.5047   |
| 1.1314        | 6.0   | 480  | 1.1844          | 0.4858   |
| 1.0789        | 7.0   | 560  | 1.1870          | 0.5142   |
| 1.0419        | 8.0   | 640  | 1.1317          | 0.5377   |
| 1.0222        | 9.0   | 720  | 1.2062          | 0.4906   |
| 1.0077        | 10.0  | 800  | 1.1582          | 0.4764   |
| 0.9161        | 11.0  | 880  | 1.1841          | 0.5047   |
| 0.9066        | 12.0  | 960  | 1.1603          | 0.5236   |
| 0.8948        | 13.0  | 1040 | 1.1681          | 0.4906   |
| 0.8382        | 14.0  | 1120 | 1.1980          | 0.4953   |
| 0.8279        | 15.0  | 1200 | 1.2145          | 0.4953   |
| 0.7839        | 16.0  | 1280 | 1.2142          | 0.5      |
| 0.7797        | 17.0  | 1360 | 1.2288          | 0.5      |
| 0.7794        | 18.0  | 1440 | 1.2374          | 0.5      |
| 0.7447        | 19.0  | 1520 | 1.2071          | 0.5047   |
| 0.7101        | 20.0  | 1600 | 1.1943          | 0.5142   |
| 0.7229        | 21.0  | 1680 | 1.1930          | 0.5142   |
| 0.6906        | 22.0  | 1760 | 1.2124          | 0.5189   |
| 0.6743        | 23.0  | 1840 | 1.2044          | 0.5283   |
| 0.7181        | 24.0  | 1920 | 1.2020          | 0.5330   |
| 0.7323        | 25.0  | 2000 | 1.2088          | 0.5236   |
| 0.6597        | 26.0  | 2080 | 1.2148          | 0.5189   |
| 0.6476        | 27.0  | 2160 | 1.2144          | 0.5189   |
| 0.6792        | 28.0  | 2240 | 1.2133          | 0.5142   |
| 0.6455        | 29.0  | 2320 | 1.2134          | 0.5283   |
| 0.6719        | 30.0  | 2400 | 1.2133          | 0.5283   |


### Framework versions

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