| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/convnext-tiny-224 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - 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: 0.9429 |
| - Logloss: 0.9429 |
| - Accuracy: {'accuracy': 0.6371511068334937} |
|
|
| ## 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 | Logloss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:-------:|:--------------------------------:| |
| | 1.4538 | 0.9846 | 32 | 1.3816 | 1.3816 | {'accuracy': 0.4475457170356112} | |
| | 1.2257 | 2.0 | 65 | 1.1411 | 1.1411 | {'accuracy': 0.5668912415784408} | |
| | 1.0432 | 2.9846 | 97 | 1.0302 | 1.0302 | {'accuracy': 0.6034648700673725} | |
| | 1.0002 | 4.0 | 130 | 0.9979 | 0.9979 | {'accuracy': 0.615014436958614} | |
| | 0.9492 | 4.9846 | 162 | 0.9781 | 0.9781 | {'accuracy': 0.631376323387873} | |
| | 0.9302 | 6.0 | 195 | 0.9664 | 0.9664 | {'accuracy': 0.629451395572666} | |
| | 0.8805 | 6.9846 | 227 | 0.9515 | 0.9515 | {'accuracy': 0.6371511068334937} | |
| | 0.852 | 8.0 | 260 | 0.9504 | 0.9504 | {'accuracy': 0.6256015399422522} | |
| | 0.8352 | 8.9846 | 292 | 0.9468 | 0.9468 | {'accuracy': 0.6371511068334937} | |
| | 0.8245 | 9.8462 | 320 | 0.9429 | 0.9429 | {'accuracy': 0.6371511068334937} | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
