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Aleksandar
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distilbert-srb-ner-setimes

Token Classification
Transformers
PyTorch
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
Aleksandar commited on
Commit
748982e
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1 Parent(s): cae2b7d

add model

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Files changed (3) hide show
  1. README.md +17 -12
  2. pytorch_model.bin +1 -1
  3. 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: 0.962385099177552
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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: 0.1354
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- - Precision: 0.8
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- - Recall: 0.8319
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- - F1: 0.8156
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- - Accuracy: 0.9624
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  ## Model description
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@@ -56,17 +56,22 @@ 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: 5
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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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- | No log | 1.0 | 207 | 0.2206 | 0.7029 | 0.7267 | 0.7146 | 0.9384 |
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- | No log | 2.0 | 414 | 0.1582 | 0.7449 | 0.7813 | 0.7627 | 0.9532 |
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- | 0.2358 | 3.0 | 621 | 0.1449 | 0.7756 | 0.8171 | 0.7958 | 0.9579 |
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- | 0.2358 | 4.0 | 828 | 0.1382 | 0.7903 | 0.8329 | 0.8110 | 0.9609 |
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- | 0.0895 | 5.0 | 1035 | 0.1354 | 0.8 | 0.8319 | 0.8156 | 0.9624 |
 
 
 
 
 
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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: 0.9660941783583293
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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: 0.1522
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+ - Precision: 0.8280
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+ - Recall: 0.8607
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+ - F1: 0.8440
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+ - Accuracy: 0.9661
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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: 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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+ | No log | 1.0 | 207 | 0.2240 | 0.6996 | 0.7200 | 0.7097 | 0.9375 |
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+ | No log | 2.0 | 414 | 0.1538 | 0.7501 | 0.7930 | 0.7710 | 0.9546 |
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+ | 0.2348 | 3.0 | 621 | 0.1459 | 0.7756 | 0.8115 | 0.7931 | 0.9576 |
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+ | 0.2348 | 4.0 | 828 | 0.1465 | 0.7918 | 0.8456 | 0.8178 | 0.9611 |
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+ | 0.0782 | 5.0 | 1035 | 0.1310 | 0.7981 | 0.8352 | 0.8162 | 0.9636 |
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+ | 0.0782 | 6.0 | 1242 | 0.1466 | 0.8103 | 0.8510 | 0.8301 | 0.9646 |
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+ | 0.0782 | 7.0 | 1449 | 0.1441 | 0.8222 | 0.8503 | 0.8360 | 0.9655 |
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+ | 0.0343 | 8.0 | 1656 | 0.1493 | 0.8265 | 0.8600 | 0.8429 | 0.9666 |
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+ | 0.0343 | 9.0 | 1863 | 0.1524 | 0.8236 | 0.8570 | 0.8400 | 0.9656 |
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+ | 0.0169 | 10.0 | 2070 | 0.1522 | 0.8280 | 0.8607 | 0.8440 | 0.9661 |
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  ### Framework versions
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