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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-huge-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: 10-convnextv2-huge-22k-384-finetuned-spiderTraining20-500 |
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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-convnextv2-huge-22k-384-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [facebook/convnextv2-huge-22k-384](https://huggingface.co/facebook/convnextv2-huge-22k-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0908 |
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- Accuracy: 0.9830 |
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- Precision: 0.9830 |
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- Recall: 0.9833 |
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- F1: 0.9830 |
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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: 5e-05 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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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: 20 |
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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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| 0.4733 | 1.0 | 399 | 0.2998 | 0.9149 | 0.9195 | 0.9099 | 0.9121 | |
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| 0.3925 | 2.0 | 799 | 0.1649 | 0.9510 | 0.9512 | 0.9502 | 0.9498 | |
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| 0.3932 | 3.0 | 1199 | 0.4475 | 0.8689 | 0.9166 | 0.8633 | 0.8785 | |
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| 0.2441 | 4.0 | 1599 | 0.1623 | 0.9469 | 0.9519 | 0.9449 | 0.9462 | |
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| 0.1249 | 5.0 | 1998 | 0.1646 | 0.9570 | 0.9609 | 0.9546 | 0.9565 | |
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| 0.2255 | 6.0 | 2398 | 0.1560 | 0.9660 | 0.9666 | 0.9644 | 0.9646 | |
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| 0.1426 | 7.0 | 2798 | 0.1115 | 0.9720 | 0.9741 | 0.9725 | 0.9731 | |
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| 0.102 | 8.0 | 3198 | 0.0927 | 0.9750 | 0.9754 | 0.9757 | 0.9754 | |
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| 0.0663 | 9.0 | 3597 | 0.0894 | 0.9820 | 0.9826 | 0.9821 | 0.9821 | |
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| 0.0556 | 9.98 | 3990 | 0.0908 | 0.9830 | 0.9830 | 0.9833 | 0.9830 | |
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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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