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ramybaly
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ner_conll2003

Token Classification
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bert
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ramybaly commited on
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add model

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Files changed (6) hide show
  1. README.md +17 -12
  2. pytorch_model.bin +1 -1
  3. runs/Aug06_21-16-58_ip-172-31-23-147/1628284640.3884907/events.out.tfevents.1628284640.ip-172-31-23-147.13610.1 +3 -0
  4. runs/Aug06_21-16-58_ip-172-31-23-147/events.out.tfevents.1628284640.ip-172-31-23-147.13610.0 +3 -0
  5. runs/Aug06_21-16-58_ip-172-31-23-147/events.out.tfevents.1628285439.ip-172-31-23-147.13610.2 +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: 0.9769764744577354
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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: 0.1551
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- - Precision: 0.8966
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- - Recall: 0.9065
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- - F1: 0.9015
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- - Accuracy: 0.9770
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  ## Model description
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@@ -62,17 +62,22 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 5
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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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- | 0.3068 | 1.0 | 877 | 0.0589 | 0.9200 | 0.9388 | 0.9293 | 0.9837 |
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- | 0.0464 | 2.0 | 1754 | 0.0562 | 0.9298 | 0.9453 | 0.9375 | 0.9851 |
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- | 0.0233 | 3.0 | 2631 | 0.0559 | 0.9408 | 0.9472 | 0.9440 | 0.9865 |
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- | 0.0116 | 4.0 | 3508 | 0.0581 | 0.9421 | 0.9523 | 0.9472 | 0.9871 |
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- | 0.0068 | 5.0 | 4385 | 0.0620 | 0.9439 | 0.9521 | 0.9480 | 0.9871 |
 
 
 
 
 
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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: 0.9764571468139249
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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: 0.1941
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+ - Precision: 0.8980
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+ - Recall: 0.9062
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+ - F1: 0.9021
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+ - Accuracy: 0.9765
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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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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+ | 0.3854 | 1.0 | 877 | 0.0670 | 0.9185 | 0.9248 | 0.9217 | 0.9818 |
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+ | 0.0578 | 2.0 | 1754 | 0.0511 | 0.9369 | 0.9484 | 0.9426 | 0.9864 |
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+ | 0.029 | 3.0 | 2631 | 0.0576 | 0.9393 | 0.9463 | 0.9428 | 0.9862 |
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+ | 0.0159 | 4.0 | 3508 | 0.0621 | 0.9373 | 0.9477 | 0.9425 | 0.9862 |
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+ | 0.0095 | 5.0 | 4385 | 0.0703 | 0.9370 | 0.9475 | 0.9422 | 0.9859 |
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+ | 0.006 | 6.0 | 5262 | 0.0728 | 0.9373 | 0.9474 | 0.9423 | 0.9860 |
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+ | 0.0042 | 7.0 | 6139 | 0.0728 | 0.9413 | 0.9529 | 0.9471 | 0.9872 |
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+ | 0.0025 | 8.0 | 7016 | 0.0783 | 0.9434 | 0.9505 | 0.9469 | 0.9868 |
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+ | 0.0017 | 9.0 | 7893 | 0.0782 | 0.9425 | 0.9532 | 0.9478 | 0.9870 |
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+ | 0.001 | 10.0 | 8770 | 0.0805 | 0.9431 | 0.9536 | 0.9483 | 0.9872 |
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  ### Framework versions
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