metadata
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_boost6
results: []
Validated_Balanced_Raw_Data_model_boost6
This model is a fine-tuned version of facebook/convnext-base-224-22k on the Logiroad/Validated_Balanced_Raw_Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.1222
- 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: 20.0
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3904 | 1.0 | 80 | 1.3300 | 0.3679 |
| 1.3255 | 2.0 | 160 | 1.2853 | 0.3868 |
| 1.2779 | 3.0 | 240 | 1.2196 | 0.4340 |
| 1.2267 | 4.0 | 320 | 1.1914 | 0.4528 |
| 1.1508 | 5.0 | 400 | 1.1553 | 0.5047 |
| 1.0964 | 6.0 | 480 | 1.2145 | 0.4764 |
| 1.0742 | 7.0 | 560 | 1.1814 | 0.5 |
| 1.0315 | 8.0 | 640 | 1.1222 | 0.5377 |
| 1.0283 | 9.0 | 720 | 1.1561 | 0.5189 |
| 0.999 | 10.0 | 800 | 1.1940 | 0.5094 |
| 0.961 | 11.0 | 880 | 1.1440 | 0.5047 |
| 0.9484 | 12.0 | 960 | 1.1716 | 0.5 |
| 0.8779 | 13.0 | 1040 | 1.1549 | 0.5142 |
| 0.8613 | 14.0 | 1120 | 1.1524 | 0.5283 |
| 0.8572 | 15.0 | 1200 | 1.1644 | 0.5189 |
| 0.8605 | 16.0 | 1280 | 1.1536 | 0.5236 |
| 0.8268 | 17.0 | 1360 | 1.1561 | 0.5283 |
| 0.8171 | 18.0 | 1440 | 1.1589 | 0.5283 |
| 0.8242 | 19.0 | 1520 | 1.1594 | 0.5236 |
| 0.7743 | 20.0 | 1600 | 1.1596 | 0.5283 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0
- Datasets 3.1.0
- Tokenizers 0.20.3