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Aleksandar
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bert-srb-ner-setimes

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
Aleksandar commited on
Commit
6e283f4
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1 Parent(s): a1fed0a

add model

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Files changed (3) hide show
  1. README.md +27 -12
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,7 +17,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9557318926219821
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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
@@ -27,11 +27,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1490
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- - Precision: 0.7643
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- - Recall: 0.7972
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- - F1: 0.7804
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- - Accuracy: 0.9557
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  ## Model description
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@@ -56,17 +56,32 @@ The following hyperparameters were used during training:
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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: 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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- | No log | 1.0 | 104 | 0.2357 | 0.6485 | 0.6922 | 0.6697 | 0.9325 |
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- | No log | 2.0 | 208 | 0.1876 | 0.7036 | 0.7440 | 0.7232 | 0.9447 |
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- | No log | 3.0 | 312 | 0.1651 | 0.7389 | 0.7739 | 0.7560 | 0.9515 |
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- | No log | 4.0 | 416 | 0.1530 | 0.7562 | 0.7888 | 0.7722 | 0.9544 |
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- | 0.2044 | 5.0 | 520 | 0.1490 | 0.7643 | 0.7972 | 0.7804 | 0.9557 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.9645112274185379
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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 was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1955
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+ - Precision: 0.8229
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+ - Recall: 0.8465
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+ - F1: 0.8345
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+ - Accuracy: 0.9645
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  ## Model description
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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: 20
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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 | 1.0 | 104 | 0.2281 | 0.6589 | 0.7001 | 0.6789 | 0.9350 |
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+ | No log | 2.0 | 208 | 0.1833 | 0.7105 | 0.7694 | 0.7388 | 0.9470 |
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+ | No log | 3.0 | 312 | 0.1573 | 0.7461 | 0.7778 | 0.7616 | 0.9525 |
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+ | No log | 4.0 | 416 | 0.1489 | 0.7665 | 0.8091 | 0.7872 | 0.9557 |
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+ | 0.1898 | 5.0 | 520 | 0.1445 | 0.7881 | 0.8327 | 0.8098 | 0.9587 |
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+ | 0.1898 | 6.0 | 624 | 0.1473 | 0.7913 | 0.8316 | 0.8109 | 0.9601 |
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+ | 0.1898 | 7.0 | 728 | 0.1558 | 0.8101 | 0.8347 | 0.8222 | 0.9620 |
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+ | 0.1898 | 8.0 | 832 | 0.1616 | 0.8026 | 0.8302 | 0.8162 | 0.9612 |
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+ | 0.1898 | 9.0 | 936 | 0.1716 | 0.8127 | 0.8409 | 0.8266 | 0.9631 |
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+ | 0.0393 | 10.0 | 1040 | 0.1751 | 0.8140 | 0.8369 | 0.8253 | 0.9628 |
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+ | 0.0393 | 11.0 | 1144 | 0.1775 | 0.8096 | 0.8420 | 0.8255 | 0.9626 |
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+ | 0.0393 | 12.0 | 1248 | 0.1763 | 0.8161 | 0.8386 | 0.8272 | 0.9636 |
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+ | 0.0393 | 13.0 | 1352 | 0.1949 | 0.8259 | 0.8400 | 0.8329 | 0.9634 |
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+ | 0.0393 | 14.0 | 1456 | 0.1842 | 0.8205 | 0.8420 | 0.8311 | 0.9642 |
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+ | 0.0111 | 15.0 | 1560 | 0.1862 | 0.8160 | 0.8493 | 0.8323 | 0.9646 |
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+ | 0.0111 | 16.0 | 1664 | 0.1989 | 0.8176 | 0.8367 | 0.8270 | 0.9627 |
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+ | 0.0111 | 17.0 | 1768 | 0.1945 | 0.8246 | 0.8409 | 0.8327 | 0.9638 |
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+ | 0.0111 | 18.0 | 1872 | 0.1997 | 0.8270 | 0.8426 | 0.8347 | 0.9634 |
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+ | 0.0111 | 19.0 | 1976 | 0.1917 | 0.8258 | 0.8491 | 0.8373 | 0.9651 |
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+ | 0.0051 | 20.0 | 2080 | 0.1955 | 0.8229 | 0.8465 | 0.8345 | 0.9645 |
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  ### Framework versions
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