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---
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
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