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ramybaly
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ner_nerd_fine

Token Classification
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PyTorch
TensorBoard
bert
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ramybaly commited on
Commit
3b87411
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1 Parent(s): d7a87fb

add model

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Files changed (6) hide show
  1. README.md +10 -10
  2. pytorch_model.bin +1 -1
  3. runs/Aug20_17-39-29_ip-172-31-23-147/1629481174.7008605/events.out.tfevents.1629481174.ip-172-31-23-147.11873.1 +3 -0
  4. runs/Aug20_17-39-29_ip-172-31-23-147/events.out.tfevents.1629481174.ip-172-31-23-147.11873.0 +3 -0
  5. runs/Aug20_17-39-29_ip-172-31-23-147/events.out.tfevents.1629486060.ip-172-31-23-147.11873.2 +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: 0.9054809270602955
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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 nerd dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3336
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- - Precision: 0.6298
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- - Recall: 0.6766
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  - F1: 0.6524
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- - Accuracy: 0.9055
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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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- | 0.6155 | 1.0 | 8235 | 0.3365 | 0.6047 | 0.6575 | 0.6300 | 0.9016 |
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- | 0.3067 | 2.0 | 16470 | 0.3174 | 0.6321 | 0.6641 | 0.6477 | 0.9065 |
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- | 0.2379 | 3.0 | 24705 | 0.3271 | 0.6335 | 0.6794 | 0.6557 | 0.9073 |
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- | 0.1835 | 4.0 | 32940 | 0.3449 | 0.6334 | 0.6755 | 0.6537 | 0.9066 |
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- | 0.139 | 5.0 | 41175 | 0.3866 | 0.6355 | 0.6771 | 0.6556 | 0.9068 |
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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: 0.9050232835369201
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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 nerd dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3373
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+ - Precision: 0.6326
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+ - Recall: 0.6734
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  - F1: 0.6524
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+ - Accuracy: 0.9050
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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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+ | 0.6219 | 1.0 | 8235 | 0.3347 | 0.6066 | 0.6581 | 0.6313 | 0.9015 |
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+ | 0.3071 | 2.0 | 16470 | 0.3165 | 0.6349 | 0.6637 | 0.6490 | 0.9060 |
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+ | 0.2384 | 3.0 | 24705 | 0.3311 | 0.6373 | 0.6769 | 0.6565 | 0.9068 |
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+ | 0.1834 | 4.0 | 32940 | 0.3414 | 0.6349 | 0.6780 | 0.6557 | 0.9069 |
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+ | 0.1392 | 5.0 | 41175 | 0.3793 | 0.6334 | 0.6775 | 0.6547 | 0.9068 |
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  ### Framework versions
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