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Aleksandar
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electra-srb-ner

Token Classification
Transformers
PyTorch
Safetensors
electra
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Aleksandar commited on
Commit
66caa2f
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1 Parent(s): 3128e5f

add model

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Files changed (4) hide show
  1. README.md +14 -20
  2. config.json +7 -7
  3. pytorch_model.bin +1 -1
  4. 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: 0.95641898994996
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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: 0.3017
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- - Precision: 0.8911
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- - Recall: 0.9081
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- - F1: 0.8995
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- - Accuracy: 0.9564
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  ## Model description
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@@ -55,27 +55,21 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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  - eval_batch_size: 8
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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: 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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- | 0.2535 | 1.0 | 1250 | 0.2015 | 0.8494 | 0.8605 | 0.8549 | 0.9376 |
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- | 0.1461 | 2.0 | 2500 | 0.1853 | 0.8800 | 0.8681 | 0.8740 | 0.9464 |
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- | 0.0914 | 3.0 | 3750 | 0.2022 | 0.8695 | 0.8912 | 0.8802 | 0.9485 |
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- | 0.0545 | 4.0 | 5000 | 0.2214 | 0.8758 | 0.8975 | 0.8865 | 0.9514 |
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- | 0.0385 | 5.0 | 6250 | 0.2536 | 0.8806 | 0.9010 | 0.8907 | 0.9523 |
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- | 0.0266 | 6.0 | 7500 | 0.2506 | 0.8834 | 0.9020 | 0.8926 | 0.9539 |
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- | 0.0133 | 7.0 | 8750 | 0.2745 | 0.8910 | 0.9057 | 0.8983 | 0.9562 |
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- | 0.0077 | 8.0 | 10000 | 0.2946 | 0.8872 | 0.9065 | 0.8968 | 0.9559 |
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- | 0.0043 | 9.0 | 11250 | 0.2931 | 0.8902 | 0.9094 | 0.8997 | 0.9567 |
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- | 0.0022 | 10.0 | 12500 | 0.3017 | 0.8911 | 0.9081 | 0.8995 | 0.9564 |
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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: 0.9500777931962491
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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: 0.1859
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+ - Precision: 0.8742
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+ - Recall: 0.8907
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+ - F1: 0.8824
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+ - Accuracy: 0.9501
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 32
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  - eval_batch_size: 8
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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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+ | 0.3627 | 1.0 | 625 | 0.2077 | 0.8382 | 0.8545 | 0.8463 | 0.9349 |
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+ | 0.1894 | 2.0 | 1250 | 0.1764 | 0.8640 | 0.8760 | 0.8700 | 0.9453 |
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+ | 0.1326 | 3.0 | 1875 | 0.1848 | 0.8618 | 0.8873 | 0.8744 | 0.9473 |
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+ | 0.0712 | 4.0 | 2500 | 0.1859 | 0.8742 | 0.8907 | 0.8824 | 0.9501 |
 
 
 
 
 
 
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  ### Framework versions
config.json CHANGED
@@ -9,13 +9,13 @@
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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- "0": "LABEL_0",
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- "1": "LABEL_1",
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- "2": "LABEL_2",
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- "3": "LABEL_3",
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- "4": "LABEL_4",
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- "5": "LABEL_5",
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- "6": "LABEL_6"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
 
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  "hidden_dropout_prob": 0.1,
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  "hidden_size": 768,
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  "id2label": {
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+ "0": "O",
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+ "1": "B-per",
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+ "2": "I-per",
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+ "3": "B-org",
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+ "4": "I-org",
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+ "5": "B-loc",
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+ "6": "I-loc"
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  },
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  "initializer_range": 0.02,
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  "intermediate_size": 3072,
pytorch_model.bin CHANGED
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training_args.bin CHANGED
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