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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-taiwanSpiders |
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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-taiwanSpiders |
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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: 0.2014 |
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- Accuracy: 0.9486 |
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- Precision: 0.9408 |
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- Recall: 0.9397 |
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- F1: 0.9395 |
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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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| 0.6309 | 1.0 | 759 | 0.4255 | 0.8779 | 0.8669 | 0.8560 | 0.8499 | |
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| 0.6529 | 2.0 | 1519 | 0.3880 | 0.8882 | 0.8728 | 0.8710 | 0.8634 | |
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| 0.53 | 3.0 | 2278 | 0.3389 | 0.9024 | 0.8953 | 0.8929 | 0.8896 | |
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| 0.4746 | 4.0 | 3038 | 0.3393 | 0.9017 | 0.9036 | 0.8868 | 0.8881 | |
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| 0.4565 | 5.0 | 3797 | 0.3061 | 0.9169 | 0.9266 | 0.9044 | 0.9094 | |
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| 0.3145 | 6.0 | 4557 | 0.2600 | 0.9282 | 0.9237 | 0.9148 | 0.9173 | |
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| 0.3034 | 7.0 | 5316 | 0.2613 | 0.9345 | 0.9306 | 0.9216 | 0.9225 | |
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| 0.2724 | 8.0 | 6076 | 0.2410 | 0.9417 | 0.9371 | 0.9312 | 0.9319 | |
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| 0.2055 | 9.0 | 6835 | 0.2127 | 0.9457 | 0.9382 | 0.9378 | 0.9370 | |
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| 0.2103 | 9.99 | 7590 | 0.2014 | 0.9486 | 0.9408 | 0.9397 | 0.9395 | |
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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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