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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-22k-224 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: convnextv2-base-22k-224-finetuned-tekno24 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# convnextv2-base-22k-224-finetuned-tekno24 |
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This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9120 |
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- Accuracy: 0.6138 |
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- F1: 0.5996 |
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- Precision: 0.5969 |
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- Recall: 0.6138 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 12 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.3179 | 0.9968 | 78 | 1.2415 | 0.4207 | 0.3979 | 0.4642 | 0.4207 | |
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| 1.1998 | 1.9936 | 156 | 1.0769 | 0.5103 | 0.4525 | 0.5309 | 0.5103 | |
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| 1.168 | 2.9904 | 234 | 1.0573 | 0.5494 | 0.5033 | 0.5605 | 0.5494 | |
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| 1.1107 | 4.0 | 313 | 0.9924 | 0.5540 | 0.5163 | 0.5257 | 0.5540 | |
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| 1.1062 | 4.9968 | 391 | 1.0018 | 0.5747 | 0.5507 | 0.5660 | 0.5747 | |
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| 1.0331 | 5.9936 | 469 | 0.9901 | 0.5931 | 0.5768 | 0.6202 | 0.5931 | |
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| 1.0409 | 6.9904 | 547 | 0.9634 | 0.5747 | 0.5723 | 0.5722 | 0.5747 | |
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| 1.0176 | 8.0 | 626 | 0.9504 | 0.5931 | 0.5834 | 0.5814 | 0.5931 | |
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| 0.995 | 8.9968 | 704 | 0.9584 | 0.5908 | 0.5854 | 0.5853 | 0.5908 | |
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| 0.9937 | 9.9936 | 782 | 0.9339 | 0.6023 | 0.5934 | 0.5894 | 0.6023 | |
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| 0.9387 | 10.9904 | 860 | 0.9120 | 0.6138 | 0.5996 | 0.5969 | 0.6138 | |
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| 0.9324 | 11.9617 | 936 | 0.9135 | 0.5954 | 0.5879 | 0.5865 | 0.5954 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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