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albert-large-v2-finetuned-abbDet-finetuned-ner

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albert
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End of training

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  1. README.md +18 -21
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [surrey-nlp/albert-large-v2-finetuned-abbDet](https://huggingface.co/surrey-nlp/albert-large-v2-finetuned-abbDet) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1013
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- - Precision: 0.9788
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- - Recall: 0.9756
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- - F1: 0.9772
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- - Accuracy: 0.9754
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  ## Model description
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@@ -44,32 +44,29 @@ More information needed
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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: 2
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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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  - num_epochs: 10
 
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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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- | No log | 0.19 | 100 | 0.1850 | 0.9561 | 0.9550 | 0.9555 | 0.9554 |
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- | No log | 0.37 | 200 | 0.1138 | 0.9716 | 0.9673 | 0.9695 | 0.9675 |
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- | No log | 0.56 | 300 | 0.1021 | 0.9753 | 0.9720 | 0.9737 | 0.9714 |
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- | No log | 0.75 | 400 | 0.1034 | 0.9758 | 0.9719 | 0.9739 | 0.9714 |
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- | 0.2096 | 0.93 | 500 | 0.0964 | 0.9775 | 0.9740 | 0.9757 | 0.9737 |
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- | 0.2096 | 1.12 | 600 | 0.0984 | 0.9781 | 0.9755 | 0.9768 | 0.9748 |
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- | 0.2096 | 1.31 | 700 | 0.1016 | 0.9786 | 0.9758 | 0.9772 | 0.9753 |
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- | 0.2096 | 1.49 | 800 | 0.1034 | 0.9781 | 0.9758 | 0.9769 | 0.9750 |
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- | 0.2096 | 1.68 | 900 | 0.1020 | 0.9775 | 0.9755 | 0.9765 | 0.9746 |
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- | 0.0669 | 1.87 | 1000 | 0.1006 | 0.9778 | 0.9749 | 0.9764 | 0.9744 |
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- | 0.0669 | 2.05 | 1100 | 0.0973 | 0.9788 | 0.9760 | 0.9774 | 0.9755 |
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- | 0.0669 | 2.24 | 1200 | 0.1013 | 0.9788 | 0.9756 | 0.9772 | 0.9754 |
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- | 0.0669 | 2.43 | 1300 | 0.0995 | 0.9782 | 0.9758 | 0.9770 | 0.9750 |
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- | 0.0669 | 2.61 | 1400 | 0.1079 | 0.9782 | 0.9759 | 0.9771 | 0.9752 |
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- | 0.051 | 2.8 | 1500 | 0.1092 | 0.9781 | 0.9760 | 0.9771 | 0.9753 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [surrey-nlp/albert-large-v2-finetuned-abbDet](https://huggingface.co/surrey-nlp/albert-large-v2-finetuned-abbDet) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0950
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+ - Precision: 0.9784
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+ - Recall: 0.9763
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+ - F1: 0.9773
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+ - Accuracy: 0.9757
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  ## Model description
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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: 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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  - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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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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+ | No log | 0.37 | 100 | 0.1655 | 0.9638 | 0.9621 | 0.9629 | 0.9622 |
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+ | No log | 0.75 | 200 | 0.1073 | 0.9752 | 0.9705 | 0.9729 | 0.9709 |
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+ | No log | 1.12 | 300 | 0.0951 | 0.9776 | 0.9742 | 0.9759 | 0.9740 |
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+ | No log | 1.49 | 400 | 0.0952 | 0.9778 | 0.9752 | 0.9765 | 0.9748 |
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+ | 0.1901 | 1.87 | 500 | 0.0948 | 0.9780 | 0.9745 | 0.9763 | 0.9746 |
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+ | 0.1901 | 2.24 | 600 | 0.0947 | 0.9788 | 0.9758 | 0.9773 | 0.9755 |
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+ | 0.1901 | 2.61 | 700 | 0.0962 | 0.9789 | 0.9766 | 0.9778 | 0.9758 |
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+ | 0.1901 | 2.99 | 800 | 0.0950 | 0.9784 | 0.9763 | 0.9773 | 0.9757 |
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+ | 0.1901 | 3.36 | 900 | 0.0984 | 0.9784 | 0.9763 | 0.9773 | 0.9755 |
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+ | 0.0493 | 3.73 | 1000 | 0.1012 | 0.9781 | 0.9759 | 0.9770 | 0.9752 |
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+ | 0.0493 | 4.1 | 1100 | 0.1029 | 0.9781 | 0.9763 | 0.9772 | 0.9754 |
 
 
 
 
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  ### Framework versions
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