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ramybaly
/
ner_conll2003

Token Classification
Transformers
PyTorch
TensorBoard
bert
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2
ramybaly commited on
Commit
c6388a1
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1 Parent(s): 1727d8c

add model

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Files changed (6) hide show
  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
  3. runs/Aug12_21-02-15_ip-172-31-23-147/1628802141.1529648/events.out.tfevents.1628802141.ip-172-31-23-147.26889.1 +3 -0
  4. runs/Aug12_21-02-15_ip-172-31-23-147/events.out.tfevents.1628802141.ip-172-31-23-147.26889.0 +3 -0
  5. runs/Aug12_21-02-15_ip-172-31-23-147/events.out.tfevents.1628802595.ip-172-31-23-147.26889.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9765783232641474
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,11 +32,11 @@ 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 the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1586
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- - Precision: 0.8954
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- - Recall: 0.9057
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- - F1: 0.9005
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- - Accuracy: 0.9766
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  ## Model description
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@@ -68,11 +68,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.3167 | 1.0 | 877 | 0.0610 | 0.9198 | 0.9342 | 0.9269 | 0.9832 |
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- | 0.0476 | 2.0 | 1754 | 0.0561 | 0.9293 | 0.9405 | 0.9349 | 0.9851 |
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- | 0.0238 | 3.0 | 2631 | 0.0564 | 0.9421 | 0.9480 | 0.9450 | 0.9867 |
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- | 0.0119 | 4.0 | 3508 | 0.0597 | 0.9436 | 0.9526 | 0.9480 | 0.9872 |
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- | 0.0074 | 5.0 | 4385 | 0.0630 | 0.9443 | 0.9556 | 0.9499 | 0.9876 |
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  ### Framework versions
 
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  metric:
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  name: Accuracy
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  type: accuracy
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+ value: 0.9770630290650372
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  ---
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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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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1491
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+ - Precision: 0.9010
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+ - Recall: 0.9084
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+ - F1: 0.9046
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+ - Accuracy: 0.9771
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.3108 | 1.0 | 877 | 0.0607 | 0.9184 | 0.9345 | 0.9264 | 0.9831 |
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+ | 0.0476 | 2.0 | 1754 | 0.0563 | 0.9362 | 0.9430 | 0.9396 | 0.9852 |
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+ | 0.0237 | 3.0 | 2631 | 0.0588 | 0.9419 | 0.9476 | 0.9448 | 0.9866 |
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+ | 0.0118 | 4.0 | 3508 | 0.0617 | 0.9444 | 0.9523 | 0.9483 | 0.9873 |
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+ | 0.007 | 5.0 | 4385 | 0.0645 | 0.9419 | 0.9505 | 0.9462 | 0.9869 |
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  ### Framework versions
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