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fold_1

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  1. README.md +18 -16
  2. model.safetensors +1 -1
README.md CHANGED
@@ -16,19 +16,21 @@ 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-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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  # fold_1
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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: 0.0113
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- - Precision: 0.8172
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- - Recall: 0.5823
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- - F1: 0.6801
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  - Accuracy: 0.9993
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- - Roc Auc: 0.9933
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- - Pr Auc: 0.9998
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  ## Model description
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@@ -53,22 +55,22 @@ 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: 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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- | 0.0326 | 1.0 | 632 | 0.0138 | 0.6507 | 0.4668 | 0.5436 | 0.9991 | 0.9909 | 0.9998 |
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- | 0.0116 | 2.0 | 1264 | 0.0113 | 0.8172 | 0.5823 | 0.6801 | 0.9993 | 0.9933 | 0.9998 |
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- | 0.0071 | 3.0 | 1896 | 0.0131 | 0.7896 | 0.5995 | 0.6816 | 0.9993 | 0.9915 | 0.9998 |
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- | 0.0023 | 4.0 | 2528 | 0.0165 | 0.6275 | 0.6953 | 0.6597 | 0.9991 | 0.9899 | 0.9998 |
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- | 0.0013 | 5.0 | 3160 | 0.0173 | 0.7465 | 0.6585 | 0.6997 | 0.9993 | 0.9827 | 0.9996 |
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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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  <!-- 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-change2/runs/zkyqf4w8)
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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-change2/runs/n6lnsbeg)
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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-change2/runs/k9jhon43)
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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-change2/runs/67sviuwh)
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  # fold_1
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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: 0.0104
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+ - Precision: 0.6792
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+ - Recall: 0.5870
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+ - F1: 0.6297
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  - Accuracy: 0.9993
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+ - Roc Auc: 0.9967
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+ - Pr Auc: 0.9999
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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: 5
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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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+ | 0.0252 | 1.0 | 711 | 0.0159 | 0.4538 | 0.6413 | 0.5315 | 0.9988 | 0.9944 | 0.9998 |
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+ | 0.0095 | 2.0 | 1422 | 0.0104 | 0.6792 | 0.5870 | 0.6297 | 0.9993 | 0.9967 | 0.9999 |
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+ | 0.003 | 3.0 | 2133 | 0.0106 | 0.6432 | 0.6957 | 0.6684 | 0.9993 | 0.9973 | 0.9999 |
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+ | 0.0024 | 4.0 | 2844 | 0.0126 | 0.7006 | 0.6739 | 0.6870 | 0.9994 | 0.9960 | 0.9999 |
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+ | 0.0004 | 5.0 | 3555 | 0.0148 | 0.7239 | 0.6413 | 0.6801 | 0.9994 | 0.9954 | 0.9999 |
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  ### Framework versions
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+ - Transformers 4.42.0.dev0
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+ - Pytorch 2.3.0+cu121
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
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