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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: facebook/convnextv2-tiny-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: convnextv2-tiny-22k-384-finetuned-spiderTraining10-1000
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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-spiderTraining10-1000
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0815
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+ - Accuracy: 0.9770
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+ - Precision: 0.9760
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+ - Recall: 0.9770
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+ - F1: 0.9763
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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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+ - 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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+ | 0.4288 | 1.0 | 125 | 0.2043 | 0.9530 | 0.9533 | 0.9524 | 0.9523 |
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+ | 0.2463 | 2.0 | 250 | 0.1362 | 0.9620 | 0.9619 | 0.9617 | 0.9612 |
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+ | 0.2434 | 3.0 | 375 | 0.0860 | 0.9710 | 0.9699 | 0.9709 | 0.9703 |
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+ | 0.1694 | 4.0 | 500 | 0.0805 | 0.9770 | 0.9763 | 0.9768 | 0.9765 |
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+ | 0.1505 | 5.0 | 625 | 0.0815 | 0.9770 | 0.9760 | 0.9770 | 0.9763 |
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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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