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Aleksandar
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distilbert-srb-ner

Token Classification
Transformers
PyTorch
Serbian
distilbert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Aleksandar commited on
Commit
5fdebf6
·
1 Parent(s): 0e09161

add model

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Files changed (3) hide show
  1. README.md +29 -13
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -21,7 +21,7 @@ model_index:
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  metric:
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  name: Accuracy
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  type: accuracy
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- value: 0.9503250498060186
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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
@@ -31,11 +31,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the wikiann dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1723
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- - Precision: 0.8667
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- - Recall: 0.8860
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- - F1: 0.8763
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- - Accuracy: 0.9503
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  ## Model description
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@@ -60,16 +60,32 @@ 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: 4
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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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- | 0.3839 | 1.0 | 625 | 0.2204 | 0.8112 | 0.8367 | 0.8238 | 0.9298 |
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- | 0.2004 | 2.0 | 1250 | 0.1805 | 0.8530 | 0.8676 | 0.8602 | 0.9442 |
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- | 0.1475 | 3.0 | 1875 | 0.1716 | 0.8536 | 0.8778 | 0.8655 | 0.9467 |
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- | 0.0943 | 4.0 | 2500 | 0.1723 | 0.8667 | 0.8860 | 0.8763 | 0.9503 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.9576561462374611
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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 wikiann dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2972
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+ - Precision: 0.8871
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+ - Recall: 0.9100
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+ - F1: 0.8984
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+ - Accuracy: 0.9577
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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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+ | 0.3818 | 1.0 | 625 | 0.2175 | 0.8175 | 0.8370 | 0.8272 | 0.9306 |
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+ | 0.198 | 2.0 | 1250 | 0.1766 | 0.8551 | 0.8732 | 0.8640 | 0.9458 |
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+ | 0.1423 | 3.0 | 1875 | 0.1702 | 0.8597 | 0.8763 | 0.8679 | 0.9473 |
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+ | 0.079 | 4.0 | 2500 | 0.1774 | 0.8674 | 0.8875 | 0.8773 | 0.9515 |
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+ | 0.0531 | 5.0 | 3125 | 0.2011 | 0.8688 | 0.8965 | 0.8825 | 0.9522 |
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+ | 0.0429 | 6.0 | 3750 | 0.2082 | 0.8769 | 0.8970 | 0.8868 | 0.9538 |
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+ | 0.032 | 7.0 | 4375 | 0.2268 | 0.8764 | 0.8916 | 0.8839 | 0.9528 |
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+ | 0.0204 | 8.0 | 5000 | 0.2423 | 0.8726 | 0.8959 | 0.8841 | 0.9529 |
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+ | 0.0148 | 9.0 | 5625 | 0.2522 | 0.8774 | 0.8991 | 0.8881 | 0.9538 |
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+ | 0.0125 | 10.0 | 6250 | 0.2544 | 0.8823 | 0.9024 | 0.8922 | 0.9559 |
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+ | 0.0108 | 11.0 | 6875 | 0.2592 | 0.8780 | 0.9041 | 0.8909 | 0.9553 |
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+ | 0.007 | 12.0 | 7500 | 0.2672 | 0.8877 | 0.9056 | 0.8965 | 0.9571 |
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+ | 0.0048 | 13.0 | 8125 | 0.2714 | 0.8879 | 0.9089 | 0.8982 | 0.9583 |
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+ | 0.0049 | 14.0 | 8750 | 0.2872 | 0.8873 | 0.9068 | 0.8970 | 0.9573 |
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+ | 0.0034 | 15.0 | 9375 | 0.2915 | 0.8883 | 0.9114 | 0.8997 | 0.9577 |
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+ | 0.0027 | 16.0 | 10000 | 0.2890 | 0.8865 | 0.9103 | 0.8983 | 0.9581 |
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+ | 0.0028 | 17.0 | 10625 | 0.2885 | 0.8877 | 0.9085 | 0.8980 | 0.9576 |
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+ | 0.0014 | 18.0 | 11250 | 0.2928 | 0.8860 | 0.9073 | 0.8965 | 0.9577 |
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+ | 0.0013 | 19.0 | 11875 | 0.2963 | 0.8856 | 0.9099 | 0.8976 | 0.9576 |
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+ | 0.001 | 20.0 | 12500 | 0.2972 | 0.8871 | 0.9100 | 0.8984 | 0.9577 |
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  ### Framework versions
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