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--- |
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license: apache-2.0 |
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base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000 |
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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: 10-finetuned-ausSpiders2000 |
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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-finetuned-ausSpiders2000 |
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This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co./zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0184 |
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- Accuracy: 0.9929 |
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- Precision: 0.9955 |
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- Recall: 0.9910 |
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- F1: 0.9932 |
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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: 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: 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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| 0.2684 | 1.0 | 141 | 0.1271 | 0.9503 | 0.9350 | 0.9199 | 0.9198 | |
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| 0.1698 | 2.0 | 282 | 0.1668 | 0.9485 | 0.9229 | 0.9195 | 0.9123 | |
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| 0.1538 | 3.0 | 423 | 0.0906 | 0.9645 | 0.9764 | 0.9365 | 0.9523 | |
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| 0.153 | 4.0 | 564 | 0.0860 | 0.9707 | 0.9685 | 0.9451 | 0.9525 | |
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| 0.0699 | 5.0 | 705 | 0.0528 | 0.9813 | 0.9830 | 0.9728 | 0.9776 | |
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| 0.1107 | 6.0 | 846 | 0.0460 | 0.9831 | 0.9832 | 0.9879 | 0.9855 | |
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| 0.0647 | 7.0 | 987 | 0.0319 | 0.9849 | 0.9905 | 0.9765 | 0.9829 | |
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| 0.0461 | 8.0 | 1128 | 0.0350 | 0.9840 | 0.9866 | 0.9710 | 0.9776 | |
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| 0.0371 | 9.0 | 1269 | 0.0198 | 0.9920 | 0.9952 | 0.9903 | 0.9927 | |
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| 0.0496 | 10.0 | 1410 | 0.0184 | 0.9929 | 0.9955 | 0.9910 | 0.9932 | |
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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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