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End of training

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README.md CHANGED
@@ -7,6 +7,7 @@ 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_0
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  results: []
@@ -15,19 +16,20 @@ model-index:
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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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  # fold_0
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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: 0.0130
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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: 0.6999
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- - Roc Auc: 0.9149
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  ## Model description
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@@ -52,17 +54,10 @@ The following hyperparameters were used during training:
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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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- | 0.0281 | 1.0 | 630 | 0.0113 | 0.3745 | 0.9507 | 0.7320 | 0.6813 | 0.9278 |
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- | 0.009 | 2.0 | 1260 | 0.0108 | 0.5987 | 0.1560 | 0.1560 | 0.5519 | 0.9242 |
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- | 0.0061 | 3.0 | 1890 | 0.0110 | 0.0581 | 0.8662 | 0.6011 | 0.6682 | 0.9283 |
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- | 0.0012 | 4.0 | 2520 | 0.0122 | 0.7081 | 0.0206 | 0.9699 | 0.7090 | 0.9146 |
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- | 0.0006 | 5.0 | 3150 | 0.0130 | 0.8324 | 0.2123 | 0.1818 | 0.6999 | 0.9149 |
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  ### Framework versions
 
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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_0
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  results: []
 
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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-DropOut/runs/efvlo6po)
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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-DropOut/runs/rlozowm0)
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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-DropOut/runs/ui7028e9)
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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-DropOut/runs/vf6fcbva)
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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-DropOut/runs/udywnxov)
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  # fold_0
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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: 1.2353
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+ - Precision: 0.0017
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+ - Recall: 0.1464
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+ - F1: 0.0034
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+ - Accuracy: 0.5619
 
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  ## Model description
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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: 0
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  ### Training results
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  ### Framework versions
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