| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: convnext-tiny-224_finetuned |
| 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. --> |
|
|
| # 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: 0.0895 |
| - Precision: 0.9807 |
| - Recall: 0.9608 |
| - F1: 0.9702 |
| - Accuracy: 0.9776 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 46 | 0.3080 | 0.9096 | 0.6852 | 0.7206 | 0.8365 | |
| | No log | 2.0 | 92 | 0.1644 | 0.9660 | 0.9176 | 0.9386 | 0.9551 | |
| | No log | 3.0 | 138 | 0.0974 | 0.9742 | 0.9586 | 0.9661 | 0.9744 | |
| | No log | 4.0 | 184 | 0.0795 | 0.9829 | 0.9670 | 0.9746 | 0.9808 | |
| | No log | 5.0 | 230 | 0.0838 | 0.9807 | 0.9608 | 0.9702 | 0.9776 | |
| | No log | 6.0 | 276 | 0.0838 | 0.9807 | 0.9608 | 0.9702 | 0.9776 | |
| | No log | 7.0 | 322 | 0.0803 | 0.9829 | 0.9670 | 0.9746 | 0.9808 | |
| | No log | 8.0 | 368 | 0.0869 | 0.9807 | 0.9608 | 0.9702 | 0.9776 | |
| | No log | 9.0 | 414 | 0.0897 | 0.9807 | 0.9608 | 0.9702 | 0.9776 | |
| | No log | 10.0 | 460 | 0.0895 | 0.9807 | 0.9608 | 0.9702 | 0.9776 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.22.1 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
| |
