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Aleksandar
/
bert-srb-ner

Token Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Aleksandar commited on
Commit
1774bdf
·
1 Parent(s): 12be85e

add model

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Files changed (4) hide show
  1. README.md +28 -18
  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: 0.9542715764169646
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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: 0.3045
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- - Precision: 0.8922
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- - Recall: 0.9050
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- - F1: 0.8986
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- - Accuracy: 0.9543
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  ## Model description
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@@ -55,27 +55,37 @@ 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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- | 0.276 | 1.0 | 1250 | 0.2359 | 0.8355 | 0.8334 | 0.8344 | 0.9276 |
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- | 0.1722 | 2.0 | 2500 | 0.2016 | 0.8731 | 0.8685 | 0.8708 | 0.9426 |
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- | 0.1155 | 3.0 | 3750 | 0.1897 | 0.8707 | 0.8860 | 0.8783 | 0.9463 |
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- | 0.0849 | 4.0 | 5000 | 0.2151 | 0.8755 | 0.8980 | 0.8866 | 0.9494 |
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- | 0.0554 | 5.0 | 6250 | 0.2373 | 0.8820 | 0.8923 | 0.8871 | 0.9495 |
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- | 0.039 | 6.0 | 7500 | 0.2644 | 0.8808 | 0.8953 | 0.8880 | 0.9505 |
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- | 0.0286 | 7.0 | 8750 | 0.2737 | 0.8915 | 0.8961 | 0.8938 | 0.9520 |
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- | 0.018 | 8.0 | 10000 | 0.2879 | 0.8860 | 0.9039 | 0.8948 | 0.9526 |
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- | 0.0116 | 9.0 | 11250 | 0.2973 | 0.8930 | 0.9032 | 0.8981 | 0.9542 |
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- | 0.0079 | 10.0 | 12500 | 0.3045 | 0.8922 | 0.9050 | 0.8986 | 0.9543 |
 
 
 
 
 
 
 
 
 
 
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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: 0.9546696220907545
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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: 0.3561
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+ - Precision: 0.8909
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+ - Recall: 0.9082
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+ - F1: 0.8995
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+ - Accuracy: 0.9547
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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: 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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+ | 0.3907 | 1.0 | 625 | 0.2316 | 0.8255 | 0.8314 | 0.8285 | 0.9259 |
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+ | 0.2091 | 2.0 | 1250 | 0.1920 | 0.8598 | 0.8731 | 0.8664 | 0.9420 |
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+ | 0.1562 | 3.0 | 1875 | 0.1833 | 0.8608 | 0.8820 | 0.8713 | 0.9441 |
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+ | 0.0919 | 4.0 | 2500 | 0.1985 | 0.8712 | 0.8886 | 0.8798 | 0.9476 |
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+ | 0.0625 | 5.0 | 3125 | 0.2195 | 0.8762 | 0.8923 | 0.8842 | 0.9485 |
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+ | 0.0545 | 6.0 | 3750 | 0.2320 | 0.8706 | 0.9004 | 0.8852 | 0.9495 |
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+ | 0.0403 | 7.0 | 4375 | 0.2459 | 0.8817 | 0.8957 | 0.8887 | 0.9505 |
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+ | 0.0269 | 8.0 | 5000 | 0.2603 | 0.8813 | 0.9021 | 0.8916 | 0.9516 |
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+ | 0.0193 | 9.0 | 5625 | 0.2916 | 0.8812 | 0.8949 | 0.8880 | 0.9500 |
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+ | 0.0162 | 10.0 | 6250 | 0.2938 | 0.8814 | 0.9025 | 0.8918 | 0.9520 |
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+ | 0.0134 | 11.0 | 6875 | 0.3330 | 0.8809 | 0.8961 | 0.8885 | 0.9497 |
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+ | 0.0076 | 12.0 | 7500 | 0.3141 | 0.8840 | 0.9025 | 0.8932 | 0.9524 |
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+ | 0.0069 | 13.0 | 8125 | 0.3292 | 0.8819 | 0.9065 | 0.8940 | 0.9535 |
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+ | 0.0053 | 14.0 | 8750 | 0.3454 | 0.8844 | 0.9018 | 0.8930 | 0.9523 |
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+ | 0.0038 | 15.0 | 9375 | 0.3519 | 0.8912 | 0.9061 | 0.8986 | 0.9539 |
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+ | 0.0034 | 16.0 | 10000 | 0.3437 | 0.8894 | 0.9038 | 0.8965 | 0.9539 |
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+ | 0.0024 | 17.0 | 10625 | 0.3518 | 0.8896 | 0.9072 | 0.8983 | 0.9543 |
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+ | 0.0018 | 18.0 | 11250 | 0.3572 | 0.8877 | 0.9072 | 0.8973 | 0.9543 |
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+ | 0.0015 | 19.0 | 11875 | 0.3554 | 0.8910 | 0.9081 | 0.8994 | 0.9549 |
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+ | 0.0011 | 20.0 | 12500 | 0.3561 | 0.8909 | 0.9082 | 0.8995 | 0.9547 |
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  ### Framework versions
config.json CHANGED
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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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