Amna100 commited on
Commit
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1 Parent(s): 3f0891a

End of training

Browse files
README.md CHANGED
@@ -1,13 +1,12 @@
1
  ---
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  license: mit
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- base_model: austin/Austin-MeDeBERTa
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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: []
@@ -16,15 +15,21 @@ 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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  # fold_2
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- This model is a fine-tuned version of [austin/Austin-MeDeBERTa](https://huggingface.co/austin/Austin-MeDeBERTa) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0102
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- - Precision: 0.6842
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- - Recall: 0.7772
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- - F1: 0.7277
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- - Accuracy: 0.9969
 
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  ## Model description
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@@ -43,26 +48,28 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-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: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0362 | 1.0 | 708 | 0.0109 | 0.6517 | 0.6304 | 0.6409 | 0.9963 |
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- | 0.0087 | 2.0 | 1416 | 0.0092 | 0.6618 | 0.7337 | 0.6959 | 0.9968 |
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- | 0.0029 | 3.0 | 2124 | 0.0102 | 0.6842 | 0.7772 | 0.7277 | 0.9969 |
 
 
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  ### Framework versions
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- - Transformers 4.39.0.dev0
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.17.1
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- - Tokenizers 0.15.2
 
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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_2
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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-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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  # 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: 0.0123
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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: 0.6254
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+ - Roc Auc: 0.9352
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  ## Model description
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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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+ | 0.0324 | 1.0 | 630 | 0.0108 | 0.3745 | 0.9507 | 0.7320 | 0.5652 | 0.9573 |
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+ | 0.0101 | 2.0 | 1260 | 0.0101 | 0.5987 | 0.1560 | 0.1560 | 0.5987 | 0.9585 |
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+ | 0.0067 | 3.0 | 1890 | 0.0114 | 0.0581 | 0.8662 | 0.6011 | 0.6210 | 0.9303 |
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+ | 0.0015 | 4.0 | 2520 | 0.0110 | 0.7081 | 0.0206 | 0.9699 | 0.5885 | 0.9400 |
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+ | 0.0006 | 5.0 | 3150 | 0.0123 | 0.8324 | 0.2123 | 0.1818 | 0.6254 | 0.9352 |
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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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