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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
2010f19
•
1 Parent(s): a4072ac

add model

Browse files
Files changed (4) hide show
  1. README.md +7 -7
  2. config.json +14 -14
  3. pytorch_model.bin +1 -1
  4. 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: 0.9314536552422759
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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: 0.2382
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- - Precision: 0.6530
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- - Recall: 0.6750
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- - F1: 0.6638
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- - Accuracy: 0.9315
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  ## Model description
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@@ -62,7 +62,7 @@ The following hyperparameters were used during training:
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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 | 207 | 0.2382 | 0.6530 | 0.6750 | 0.6638 | 0.9315 |
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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: 0.9328380888063481
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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: 0.2384
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+ - Precision: 0.6528
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+ - Recall: 0.6863
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+ - F1: 0.6691
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+ - Accuracy: 0.9328
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  ## Model description
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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 | 207 | 0.2384 | 0.6528 | 0.6863 | 0.6691 | 0.9328 |
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  ### Framework versions
config.json CHANGED
@@ -9,20 +9,6 @@
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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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- "B-deriv-per": 9,
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- "B-loc": 5,
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- "B-misc": 7,
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- "B-org": 3,
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- "B-per": 1,
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- "I-loc": 6,
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- "I-misc": 8,
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- "I-org": 4,
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- "I-per": 2,
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- "O": 0
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- },
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- "initializer_range": 0.02,
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- "intermediate_size": 3072,
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- "label2id": {
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  "0": "O",
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  "1": "B-per",
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  "2": "I-per",
@@ -34,6 +20,20 @@
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  "8": "I-misc",
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  "9": "B-deriv-per"
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  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "layer_norm_eps": 1e-12,
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  "max_position_embeddings": 512,
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  "model_type": "bert",
 
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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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  "8": "I-misc",
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  "9": "B-deriv-per"
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  },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "B-deriv-per": 9,
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+ "B-loc": 5,
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+ "B-misc": 7,
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+ "B-org": 3,
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+ "B-per": 1,
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+ "I-loc": 6,
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+ "I-misc": 8,
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+ "I-org": 4,
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+ "I-per": 2,
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+ "O": 0
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+ },
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  "layer_norm_eps": 1e-12,
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  "max_position_embeddings": 512,
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  "model_type": "bert",
pytorch_model.bin CHANGED
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