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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: zkdeng/convnextv2-tiny-22k-384-finetuned-spiderTraining100-1000
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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: convnextv2-tiny-22k-384-finetuned-spiderTraining100-1000-finetuned-spiderTraining5-100
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+ results: []
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+ ---
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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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+
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+ # convnextv2-tiny-22k-384-finetuned-spiderTraining100-1000-finetuned-spiderTraining5-100
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+
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+ This model is a fine-tuned version of [zkdeng/convnextv2-tiny-22k-384-finetuned-spiderTraining100-1000](https://huggingface.co/zkdeng/convnextv2-tiny-22k-384-finetuned-spiderTraining100-1000) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0366
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+ - Accuracy: 1.0
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+ - Precision: 1.0
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+ - Recall: 1.0
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+ - F1: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - distributed_type: multi-GPU
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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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.96 | 6 | 0.5551 | 0.9 | 0.9179 | 0.9121 | 0.9036 |
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+ | 1.3767 | 1.92 | 12 | 0.0946 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 1.3767 | 2.88 | 18 | 0.0439 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.1899 | 4.0 | 25 | 0.0412 | 0.98 | 0.975 | 0.9833 | 0.9780 |
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+ | 0.1423 | 4.8 | 30 | 0.0366 | 1.0 | 1.0 | 1.0 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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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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