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README.md
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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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