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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_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
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