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--- |
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license: mit |
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base_model: Amna100/PreTraining-MLM |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: fold_2 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-Repeatedfold/runs/lvieenf2) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-Repeatedfold/runs/fgis28rc) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-Repeatedfold/runs/9tw0vsla) |
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# fold_2 |
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This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0108 |
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- Precision: 0.6774 |
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- Recall: 0.616 |
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- F1: 0.6453 |
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- Accuracy: 0.9992 |
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- Roc Auc: 0.9952 |
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- Pr Auc: 0.9999 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:| |
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| 0.0322 | 1.0 | 632 | 0.0118 | 0.6869 | 0.544 | 0.6071 | 0.9992 | 0.9956 | 0.9999 | |
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| 0.0115 | 2.0 | 1264 | 0.0108 | 0.6774 | 0.616 | 0.6453 | 0.9992 | 0.9952 | 0.9999 | |
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| 0.0071 | 3.0 | 1896 | 0.0115 | 0.6253 | 0.7387 | 0.6773 | 0.9992 | 0.9960 | 0.9999 | |
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| 0.0028 | 4.0 | 2528 | 0.0134 | 0.7723 | 0.624 | 0.6903 | 0.9994 | 0.9943 | 0.9999 | |
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| 0.0015 | 5.0 | 3160 | 0.0137 | 0.7240 | 0.7413 | 0.7325 | 0.9994 | 0.9938 | 0.9998 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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