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README.md
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---
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license: apache-2.0
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base_model: facebook/convnextv2-huge-22k-384
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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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- precision
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- recall
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- f1
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model-index:
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- name: 10-convnextv2-huge-22k-384-finetuned-spiderTraining20-500
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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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# 10-convnextv2-huge-22k-384-finetuned-spiderTraining20-500
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This model is a fine-tuned version of [facebook/convnextv2-huge-22k-384](https://huggingface.co/facebook/convnextv2-huge-22k-384) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0908
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- Accuracy: 0.9830
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- Precision: 0.9830
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- Recall: 0.9833
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- F1: 0.9830
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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: 5
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- eval_batch_size: 5
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- seed: 42
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 20
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.4733 | 1.0 | 399 | 0.2998 | 0.9149 | 0.9195 | 0.9099 | 0.9121 |
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| 0.3925 | 2.0 | 799 | 0.1649 | 0.9510 | 0.9512 | 0.9502 | 0.9498 |
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| 0.3932 | 3.0 | 1199 | 0.4475 | 0.8689 | 0.9166 | 0.8633 | 0.8785 |
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| 0.2441 | 4.0 | 1599 | 0.1623 | 0.9469 | 0.9519 | 0.9449 | 0.9462 |
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| 0.1249 | 5.0 | 1998 | 0.1646 | 0.9570 | 0.9609 | 0.9546 | 0.9565 |
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| 0.2255 | 6.0 | 2398 | 0.1560 | 0.9660 | 0.9666 | 0.9644 | 0.9646 |
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| 0.1426 | 7.0 | 2798 | 0.1115 | 0.9720 | 0.9741 | 0.9725 | 0.9731 |
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| 0.102 | 8.0 | 3198 | 0.0927 | 0.9750 | 0.9754 | 0.9757 | 0.9754 |
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| 0.0663 | 9.0 | 3597 | 0.0894 | 0.9820 | 0.9826 | 0.9821 | 0.9821 |
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| 0.0556 | 9.98 | 3990 | 0.0908 | 0.9830 | 0.9830 | 0.9833 | 0.9830 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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