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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-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-base-22k-384-finetuned-spiderTraining50-200 |
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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-base-22k-384-finetuned-spiderTraining50-200 |
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This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2953 |
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- Accuracy: 0.9179 |
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- Precision: 0.9143 |
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- Recall: 0.9169 |
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- F1: 0.9135 |
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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: 27 |
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- eval_batch_size: 27 |
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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: 108 |
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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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| 1.2896 | 1.0 | 74 | 0.9797 | 0.7057 | 0.7360 | 0.7011 | 0.6843 | |
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| 1.1398 | 1.99 | 148 | 0.9558 | 0.7227 | 0.7691 | 0.7254 | 0.7197 | |
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| 0.7899 | 2.99 | 222 | 0.6987 | 0.7948 | 0.8101 | 0.7890 | 0.7866 | |
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| 0.5357 | 4.0 | 297 | 0.6526 | 0.8148 | 0.8327 | 0.8161 | 0.8104 | |
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| 0.4807 | 5.0 | 371 | 0.5543 | 0.8398 | 0.8512 | 0.8407 | 0.8367 | |
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| 0.3575 | 5.99 | 445 | 0.4465 | 0.8789 | 0.8814 | 0.8790 | 0.8746 | |
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| 0.3728 | 6.99 | 519 | 0.4344 | 0.8819 | 0.8840 | 0.8794 | 0.8772 | |
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| 0.2892 | 8.0 | 594 | 0.3911 | 0.8859 | 0.8879 | 0.8839 | 0.8804 | |
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| 0.2082 | 9.0 | 668 | 0.3256 | 0.9079 | 0.9067 | 0.9091 | 0.9053 | |
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| 0.1737 | 9.97 | 740 | 0.2953 | 0.9179 | 0.9143 | 0.9169 | 0.9135 | |
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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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