--- library_name: transformers license: apache-2.0 base_model: facebook/convnext-tiny-224 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: convnext-tiny-224-finetuned results: [] --- # convnext-tiny-224-finetuned This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9272 - Accuracy: 0.6275 - Precision: 0.6426 - Recall: 0.6275 - F1: 0.6068 ## 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 1.281 | 0.9846 | 32 | 1.2165 | 0.5428 | 0.5230 | 0.5428 | 0.4989 | | 1.0964 | 2.0 | 65 | 1.0549 | 0.5823 | 0.5459 | 0.5823 | 0.5427 | | 0.9929 | 2.9846 | 97 | 0.9905 | 0.6169 | 0.5755 | 0.6169 | 0.5848 | | 0.9804 | 4.0 | 130 | 0.9691 | 0.6131 | 0.5734 | 0.6131 | 0.5867 | | 0.9389 | 4.9846 | 162 | 0.9539 | 0.6246 | 0.5874 | 0.6246 | 0.6007 | | 0.9078 | 6.0 | 195 | 0.9536 | 0.6189 | 0.5910 | 0.6189 | 0.5973 | | 0.8741 | 6.9846 | 227 | 0.9333 | 0.6333 | 0.5947 | 0.6333 | 0.6098 | | 0.8523 | 8.0 | 260 | 0.9322 | 0.6323 | 0.5952 | 0.6323 | 0.6122 | | 0.8222 | 8.9846 | 292 | 0.9354 | 0.6198 | 0.6361 | 0.6198 | 0.5992 | | 0.7975 | 9.8462 | 320 | 0.9272 | 0.6275 | 0.6426 | 0.6275 | 0.6068 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1