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pingkeest
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newly_fine_tuned_bert

Text Classification
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bert
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  1. README.md +13 -18
  2. model.safetensors +1 -1
  3. runs/Jan20_16-37-43_PingkeePC/events.out.tfevents.1737362266.PingkeePC +2 -2
README.md CHANGED
@@ -19,9 +19,9 @@ 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: 0.0840
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- - F1: 0.1667
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- - Roc Auc: 0.5493
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  - Accuracy: 0.1
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  ## Model description
@@ -47,24 +47,19 @@ 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: 500
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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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- | 0.0668 | 40.0 | 920 | 0.0718 | 0.0 | 0.5 | 0.0 |
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- | 0.0507 | 80.0 | 1840 | 0.0689 | 0.0 | 0.5 | 0.0 |
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- | 0.0323 | 120.0 | 2760 | 0.0676 | 0.1818 | 0.55 | 0.1 |
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- | 0.0203 | 160.0 | 3680 | 0.0671 | 0.1818 | 0.55 | 0.1 |
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- | 0.0134 | 200.0 | 4600 | 0.0694 | 0.1818 | 0.55 | 0.1 |
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- | 0.0097 | 240.0 | 5520 | 0.0726 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0072 | 280.0 | 6440 | 0.0755 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0056 | 320.0 | 7360 | 0.0764 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0045 | 360.0 | 8280 | 0.0791 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0037 | 400.0 | 9200 | 0.0811 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0033 | 440.0 | 10120 | 0.0832 | 0.1667 | 0.5493 | 0.1 |
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- | 0.0031 | 480.0 | 11040 | 0.0840 | 0.1667 | 0.5493 | 0.1 |
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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: 0.0720
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+ - F1: 0.1818
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+ - Roc Auc: 0.55
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  - Accuracy: 0.1
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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: 300
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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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+ | 0.0677 | 40.0 | 920 | 0.0716 | 0.0 | 0.5 | 0.0 |
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+ | 0.0536 | 80.0 | 1840 | 0.0689 | 0.0 | 0.5 | 0.0 |
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+ | 0.0365 | 120.0 | 2760 | 0.0667 | 0.1818 | 0.55 | 0.1 |
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+ | 0.0255 | 160.0 | 3680 | 0.0674 | 0.1818 | 0.55 | 0.1 |
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+ | 0.0191 | 200.0 | 4600 | 0.0692 | 0.1818 | 0.55 | 0.1 |
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+ | 0.0158 | 240.0 | 5520 | 0.0711 | 0.1818 | 0.55 | 0.1 |
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+ | 0.0143 | 280.0 | 6440 | 0.0720 | 0.1818 | 0.55 | 0.1 |
 
 
 
 
 
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  ### Framework versions
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