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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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model-index: |
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- name: fold_3 |
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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-change1/runs/94wgcdtp) |
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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-change1/runs/8g0cixov) |
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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-change1/runs/05nc4r5u) |
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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-change1/runs/2tfkcyde) |
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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-change1/runs/2zf1k4id) |
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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-change1/runs/qyo3k3m3) |
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# fold_3 |
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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: 0.0185 |
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- Precision: 0.1834 |
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- Recall: 0.3042 |
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- F1: 0.5248 |
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- Pr Auc: 0.6009 |
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- Roc Auc: 0.8987 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Pr Auc | Roc Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:-------:| |
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| 0.0306 | 1.0 | 630 | 0.0134 | 0.3745 | 0.9507 | 0.7320 | 0.6102 | 0.9543 | |
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| 0.01 | 2.0 | 1260 | 0.0119 | 0.5987 | 0.1560 | 0.1560 | 0.5802 | 0.9372 | |
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| 0.0057 | 3.0 | 1890 | 0.0131 | 0.0581 | 0.8662 | 0.6011 | 0.5880 | 0.9473 | |
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| 0.0013 | 4.0 | 2520 | 0.0173 | 0.7081 | 0.0206 | 0.9699 | 0.6219 | 0.9066 | |
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| 0.0006 | 5.0 | 3150 | 0.0185 | 0.8324 | 0.2123 | 0.1818 | 0.6009 | 0.8987 | |
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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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