| --- |
| 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: [] |
| --- |
| |
| <!-- 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: 0.9272 |
| - 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 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
