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Ghunghru
/
gbert-base

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +13 -13
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9439
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- - F1: 0.3929
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  ## Model description
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@@ -37,7 +37,7 @@ 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: 8
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  - eval_batch_size: 8
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.7204 | 1.0 | 189 | 0.5750 | 0.3404 |
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- | 0.5887 | 2.0 | 378 | 0.7663 | 0.4167 |
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- | 0.5511 | 3.0 | 567 | 1.1891 | 0.4082 |
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- | 0.3559 | 4.0 | 756 | 1.2218 | 0.3448 |
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- | 0.2374 | 5.0 | 945 | 1.5306 | 0.3636 |
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- | 0.1324 | 6.0 | 1134 | 1.7488 | 0.3571 |
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- | 0.0589 | 7.0 | 1323 | 1.8829 | 0.3774 |
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- | 0.0425 | 8.0 | 1512 | 1.8652 | 0.3860 |
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- | 0.0263 | 9.0 | 1701 | 1.9057 | 0.3793 |
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- | 0.0356 | 10.0 | 1890 | 1.9439 | 0.3929 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [deepset/gbert-base](https://huggingface.co/deepset/gbert-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6440
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+ - F1: 0.5000
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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: 2e-06
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.6646 | 1.0 | 189 | 0.6565 | 0.0 |
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+ | 0.6782 | 2.0 | 378 | 0.6109 | 0.0571 |
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+ | 0.6599 | 3.0 | 567 | 0.6795 | 0.15 |
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+ | 0.6787 | 4.0 | 756 | 0.7366 | 0.15 |
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+ | 0.7246 | 5.0 | 945 | 0.6123 | 0.3830 |
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+ | 0.5843 | 6.0 | 1134 | 0.7366 | 0.2791 |
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+ | 0.6262 | 7.0 | 1323 | 0.6113 | 0.4906 |
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+ | 0.533 | 8.0 | 1512 | 0.6608 | 0.4400 |
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+ | 0.5766 | 9.0 | 1701 | 0.6496 | 0.4706 |
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+ | 0.5402 | 10.0 | 1890 | 0.6440 | 0.5000 |
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  ### Framework versions
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