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ramybaly
/
ner_nerd

Token Classification
Transformers
PyTorch
TensorBoard
bert
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2
ramybaly commited on
Commit
a988f22
·
1 Parent(s): dc61a5f

add model

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Files changed (6) hide show
  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
  3. runs/Aug07_03-09-39_ip-172-31-23-147/1628305793.3424473/events.out.tfevents.1628305793.ip-172-31-23-147.11667.1 +3 -0
  4. runs/Aug07_03-09-39_ip-172-31-23-147/events.out.tfevents.1628305793.ip-172-31-23-147.11667.0 +3 -0
  5. runs/Aug07_03-09-39_ip-172-31-23-147/events.out.tfevents.1628310023.ip-172-31-23-147.11667.2 +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: 0.9389165843185125
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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: 0.2553
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- - Precision: 0.7495
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- - Recall: 0.7859
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- - F1: 0.7672
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- - Accuracy: 0.9389
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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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- | 0.2805 | 1.0 | 8235 | 0.1950 | 0.7355 | 0.7835 | 0.7587 | 0.9376 |
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- | 0.165 | 2.0 | 16470 | 0.1919 | 0.7528 | 0.7826 | 0.7674 | 0.9400 |
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- | 0.1214 | 3.0 | 24705 | 0.2124 | 0.7522 | 0.7859 | 0.7687 | 0.9395 |
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- | 0.0879 | 4.0 | 32940 | 0.2259 | 0.7483 | 0.7879 | 0.7675 | 0.9391 |
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- | 0.0652 | 5.0 | 41175 | 0.2550 | 0.7522 | 0.7874 | 0.7694 | 0.9390 |
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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: 0.9391592461061087
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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: 0.2245
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+ - Precision: 0.7466
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+ - Recall: 0.7873
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+ - F1: 0.7664
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+ - Accuracy: 0.9392
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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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+ | 0.2843 | 1.0 | 8235 | 0.1951 | 0.7352 | 0.7824 | 0.7580 | 0.9375 |
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+ | 0.1655 | 2.0 | 16470 | 0.1928 | 0.7519 | 0.7827 | 0.7670 | 0.9398 |
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+ | 0.1216 | 3.0 | 24705 | 0.2119 | 0.75 | 0.7876 | 0.7684 | 0.9396 |
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+ | 0.0881 | 4.0 | 32940 | 0.2258 | 0.7515 | 0.7896 | 0.7701 | 0.9392 |
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+ | 0.0652 | 5.0 | 41175 | 0.2564 | 0.7518 | 0.7875 | 0.7692 | 0.9387 |
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  ### Framework versions
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