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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
0e09161
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1 Parent(s): 7a3247d

add model

Browse files
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: 0.9570619691726958
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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: 0.2532
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- - Precision: 0.8859
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- - Recall: 0.9066
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- - F1: 0.8962
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- - Accuracy: 0.9571
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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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- | 0.2615 | 1.0 | 1250 | 0.2126 | 0.8268 | 0.8327 | 0.8297 | 0.9319 |
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- | 0.1568 | 2.0 | 2500 | 0.1775 | 0.8695 | 0.8699 | 0.8697 | 0.9472 |
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- | 0.1017 | 3.0 | 3750 | 0.1718 | 0.8649 | 0.8857 | 0.8752 | 0.9504 |
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- | 0.066 | 4.0 | 5000 | 0.1906 | 0.8734 | 0.8930 | 0.8831 | 0.9530 |
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- | 0.0413 | 5.0 | 6250 | 0.2076 | 0.8805 | 0.8992 | 0.8897 | 0.9549 |
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- | 0.03 | 6.0 | 7500 | 0.2257 | 0.8758 | 0.9045 | 0.8899 | 0.9554 |
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- | 0.0213 | 7.0 | 8750 | 0.2286 | 0.8864 | 0.9015 | 0.8939 | 0.9556 |
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- | 0.0157 | 8.0 | 10000 | 0.2454 | 0.8874 | 0.9021 | 0.8947 | 0.9566 |
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- | 0.01 | 9.0 | 11250 | 0.2486 | 0.8878 | 0.9043 | 0.8960 | 0.9573 |
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- | 0.0076 | 10.0 | 12500 | 0.2532 | 0.8859 | 0.9066 | 0.8962 | 0.9571 |
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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: 0.9503250498060186
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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
 
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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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  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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+ | 0.3839 | 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
config.json CHANGED
@@ -9,13 +9,13 @@
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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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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  "label2id": {
 
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  "dropout": 0.1,
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  "hidden_dim": 3072,
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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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  "label2id": {
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