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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-ausSpiders |
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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-ausSpiders |
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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: 0.0399 |
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- Accuracy: 0.9896 |
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- Precision: 0.9831 |
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- Recall: 0.9577 |
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- F1: 0.9683 |
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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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| 0.1696 | 1.0 | 767 | 0.1719 | 0.9477 | 0.9104 | 0.8399 | 0.8558 | |
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| 0.114 | 2.0 | 1534 | 0.0823 | 0.9754 | 0.9637 | 0.8941 | 0.9185 | |
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| 0.1065 | 3.0 | 2301 | 0.0857 | 0.9708 | 0.8828 | 0.8472 | 0.8572 | |
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| 0.112 | 4.0 | 3069 | 0.0781 | 0.9756 | 0.9361 | 0.8767 | 0.8803 | |
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| 0.1006 | 5.0 | 3836 | 0.0610 | 0.9821 | 0.9662 | 0.9362 | 0.9485 | |
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| 0.0838 | 6.0 | 4603 | 0.0571 | 0.9817 | 0.9397 | 0.9442 | 0.9380 | |
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| 0.0766 | 7.0 | 5370 | 0.0507 | 0.9832 | 0.9626 | 0.9175 | 0.9302 | |
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| 0.0523 | 8.0 | 6138 | 0.0398 | 0.9870 | 0.9470 | 0.9763 | 0.9577 | |
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| 0.0531 | 9.0 | 6905 | 0.0456 | 0.9892 | 0.9881 | 0.9556 | 0.9697 | |
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| 0.0419 | 10.0 | 7670 | 0.0399 | 0.9896 | 0.9831 | 0.9577 | 0.9683 | |
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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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