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20-finetuned-spiderTraining50-200

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convnextv2
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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: 20-finetuned-spiderTraining50-200
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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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+ # 20-finetuned-spiderTraining50-200
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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: 0.4409
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+ - Accuracy: 0.8909
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+ - Precision: 0.8899
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+ - Recall: 0.8922
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+ - F1: 0.8881
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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: 0.0005
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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: 20
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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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+ | 1.4597 | 1.0 | 125 | 1.1828 | 0.6617 | 0.7065 | 0.6632 | 0.6495 |
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+ | 1.2938 | 2.0 | 250 | 1.0667 | 0.6827 | 0.7244 | 0.6845 | 0.6701 |
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+ | 1.1316 | 3.0 | 375 | 0.9465 | 0.7257 | 0.7828 | 0.7291 | 0.7280 |
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+ | 0.7827 | 4.0 | 500 | 0.8576 | 0.7397 | 0.7701 | 0.7394 | 0.7372 |
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+ | 0.7407 | 5.0 | 625 | 0.8084 | 0.7728 | 0.7876 | 0.7728 | 0.7636 |
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+ | 0.6481 | 6.0 | 750 | 0.7537 | 0.7798 | 0.7999 | 0.7783 | 0.7765 |
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+ | 0.5868 | 7.0 | 875 | 0.6406 | 0.8258 | 0.8341 | 0.8266 | 0.8224 |
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+ | 0.4461 | 8.0 | 1000 | 0.7555 | 0.7768 | 0.7953 | 0.7736 | 0.7679 |
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+ | 0.4984 | 9.0 | 1125 | 0.6601 | 0.8128 | 0.8260 | 0.8120 | 0.8059 |
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+ | 0.3898 | 10.0 | 1250 | 0.7017 | 0.8108 | 0.8296 | 0.8079 | 0.8059 |
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+ | 0.3262 | 11.0 | 1375 | 0.6199 | 0.8258 | 0.8341 | 0.8268 | 0.8212 |
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+ | 0.3243 | 12.0 | 1500 | 0.6561 | 0.8188 | 0.8316 | 0.8256 | 0.8191 |
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+ | 0.2914 | 13.0 | 1625 | 0.6037 | 0.8368 | 0.8504 | 0.8429 | 0.8351 |
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+ | 0.2627 | 14.0 | 1750 | 0.5609 | 0.8529 | 0.8588 | 0.8557 | 0.8501 |
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+ | 0.2457 | 15.0 | 1875 | 0.5266 | 0.8639 | 0.8674 | 0.8666 | 0.8613 |
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+ | 0.2294 | 16.0 | 2000 | 0.5475 | 0.8589 | 0.8658 | 0.8608 | 0.8560 |
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+ | 0.2088 | 17.0 | 2125 | 0.4929 | 0.8699 | 0.8726 | 0.8678 | 0.8672 |
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+ | 0.2101 | 18.0 | 2250 | 0.4488 | 0.8799 | 0.8782 | 0.8775 | 0.8752 |
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+ | 0.1767 | 19.0 | 2375 | 0.4543 | 0.8829 | 0.8824 | 0.8808 | 0.8782 |
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+ | 0.1445 | 20.0 | 2500 | 0.4409 | 0.8909 | 0.8899 | 0.8922 | 0.8881 |
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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