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pingkeest
/
newly_fine_tuned_bert

Text Classification
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bert
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  1. README.md +18 -9
  2. model.safetensors +1 -1
  3. runs/Jan20_16-07-50_PingkeePC/events.out.tfevents.1737360473.PingkeePC +2 -2
README.md CHANGED
@@ -19,7 +19,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0694
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  - F1: 0.0
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  - Roc Auc: 0.5
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  - Accuracy: 0.0
@@ -41,9 +41,9 @@ 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: 1e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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
@@ -51,11 +51,20 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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- |:-------------:|:--------:|:----:|:---------------:|:---:|:-------:|:--------:|
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- | 0.0752 | 153.3333 | 920 | 0.0752 | 0.0 | 0.5 | 0.0 |
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- | 0.0653 | 306.6667 | 1840 | 0.0703 | 0.0 | 0.5 | 0.0 |
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- | 0.0605 | 460.0 | 2760 | 0.0694 | 0.0 | 0.5 | 0.0 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0777
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  - F1: 0.0
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  - Roc Auc: 0.5
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  - Accuracy: 0.0
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-06
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---:|:-------:|:--------:|
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+ | 0.3837 | 40.0 | 920 | 0.3649 | 0.0 | 0.5 | 0.0 |
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+ | 0.237 | 80.0 | 1840 | 0.2244 | 0.0 | 0.5 | 0.0 |
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+ | 0.1609 | 120.0 | 2760 | 0.1560 | 0.0 | 0.5 | 0.0 |
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+ | 0.1245 | 160.0 | 3680 | 0.1210 | 0.0 | 0.5 | 0.0 |
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+ | 0.1029 | 200.0 | 4600 | 0.1022 | 0.0 | 0.5 | 0.0 |
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+ | 0.0913 | 240.0 | 5520 | 0.0916 | 0.0 | 0.5 | 0.0 |
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+ | 0.0847 | 280.0 | 6440 | 0.0854 | 0.0 | 0.5 | 0.0 |
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+ | 0.0799 | 320.0 | 7360 | 0.0818 | 0.0 | 0.5 | 0.0 |
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+ | 0.0779 | 360.0 | 8280 | 0.0798 | 0.0 | 0.5 | 0.0 |
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+ | 0.0756 | 400.0 | 9200 | 0.0786 | 0.0 | 0.5 | 0.0 |
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+ | 0.0746 | 440.0 | 10120 | 0.0780 | 0.0 | 0.5 | 0.0 |
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+ | 0.0742 | 480.0 | 11040 | 0.0777 | 0.0 | 0.5 | 0.0 |
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  ### Framework versions
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