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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-tiny-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: convnextv2-tiny-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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# convnextv2-tiny-22k-384-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2472 |
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- Accuracy: 0.9279 |
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- Precision: 0.9271 |
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- Recall: 0.9247 |
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- F1: 0.9247 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 5 |
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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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| 0.9602 | 1.0 | 125 | 0.7123 | 0.8148 | 0.8207 | 0.8080 | 0.8050 | |
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| 0.5216 | 2.0 | 250 | 0.3843 | 0.8909 | 0.8921 | 0.8893 | 0.8881 | |
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| 0.4456 | 3.0 | 375 | 0.2864 | 0.9179 | 0.9168 | 0.9099 | 0.9116 | |
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| 0.3673 | 4.0 | 500 | 0.2652 | 0.9229 | 0.9229 | 0.9200 | 0.9201 | |
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| 0.3069 | 5.0 | 625 | 0.2472 | 0.9279 | 0.9271 | 0.9247 | 0.9247 | |
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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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