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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-atto-1k-224 |
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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-atto-1k-224-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-atto-1k-224-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [facebook/convnextv2-atto-1k-224](https://huggingface.co/facebook/convnextv2-atto-1k-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4791 |
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- Accuracy: 0.8408 |
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- Precision: 0.8390 |
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- Recall: 0.8394 |
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- F1: 0.8383 |
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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: 25 |
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- eval_batch_size: 25 |
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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: 100 |
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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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| 1.8923 | 1.0 | 80 | 1.6643 | 0.4955 | 0.5096 | 0.4901 | 0.4754 | |
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| 1.0142 | 2.0 | 160 | 0.8840 | 0.7347 | 0.7512 | 0.7309 | 0.7279 | |
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| 0.8541 | 3.0 | 240 | 0.7184 | 0.7638 | 0.7659 | 0.7570 | 0.7554 | |
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| 0.7463 | 4.0 | 320 | 0.6199 | 0.8058 | 0.8057 | 0.8044 | 0.8005 | |
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| 0.6316 | 5.0 | 400 | 0.5719 | 0.8308 | 0.8344 | 0.8283 | 0.8277 | |
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| 0.576 | 6.0 | 480 | 0.5260 | 0.8258 | 0.8251 | 0.8211 | 0.8216 | |
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| 0.5158 | 7.0 | 560 | 0.5165 | 0.8428 | 0.8413 | 0.8397 | 0.8386 | |
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| 0.4545 | 8.0 | 640 | 0.4952 | 0.8428 | 0.8427 | 0.8400 | 0.8405 | |
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| 0.4602 | 9.0 | 720 | 0.4858 | 0.8418 | 0.8386 | 0.8388 | 0.8378 | |
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| 0.4606 | 10.0 | 800 | 0.4791 | 0.8408 | 0.8390 | 0.8394 | 0.8383 | |
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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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