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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_boost4
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_boost4
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: 1.1481
- Accuracy: 0.5330
## 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 | 1.2420 | 0.4151 |
| 1.2151 | 4.0 | 320 | 1.1928 | 0.4481 |
| 1.1703 | 5.0 | 400 | 1.1871 | 0.4906 |
| 1.1426 | 6.0 | 480 | 1.1827 | 0.4811 |
| 1.0837 | 7.0 | 560 | 1.1960 | 0.5094 |
| 1.0393 | 8.0 | 640 | 1.1481 | 0.5330 |
| 1.0316 | 9.0 | 720 | 1.1935 | 0.4858 |
| 1.0134 | 10.0 | 800 | 1.1634 | 0.4953 |
| 0.9324 | 11.0 | 880 | 1.1869 | 0.5094 |
| 0.9005 | 12.0 | 960 | 1.1605 | 0.4858 |
| 0.8917 | 13.0 | 1040 | 1.1818 | 0.4858 |
| 0.8299 | 14.0 | 1120 | 1.1759 | 0.4953 |
| 0.8314 | 15.0 | 1200 | 1.1999 | 0.4906 |
| 0.7891 | 16.0 | 1280 | 1.2111 | 0.5 |
| 0.7702 | 17.0 | 1360 | 1.2256 | 0.4764 |
| 0.7821 | 18.0 | 1440 | 1.2364 | 0.5142 |
| 0.7391 | 19.0 | 1520 | 1.2108 | 0.5047 |
| 0.7078 | 20.0 | 1600 | 1.1987 | 0.5 |
| 0.7245 | 21.0 | 1680 | 1.1981 | 0.5283 |
| 0.6822 | 22.0 | 1760 | 1.2110 | 0.5283 |
| 0.6646 | 23.0 | 1840 | 1.2095 | 0.5330 |
| 0.7144 | 24.0 | 1920 | 1.2078 | 0.5236 |
| 0.7271 | 25.0 | 2000 | 1.2088 | 0.5189 |
| 0.6563 | 26.0 | 2080 | 1.2137 | 0.5094 |
| 0.6447 | 27.0 | 2160 | 1.2157 | 0.5236 |
| 0.6763 | 28.0 | 2240 | 1.2135 | 0.5189 |
| 0.6434 | 29.0 | 2320 | 1.2137 | 0.5189 |
| 0.6727 | 30.0 | 2400 | 1.2136 | 0.5189 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3
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