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mor40
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BulBERT-ner-bsnlp

Token Classification
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PyTorch
bert
Generated from Trainer
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  ---
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- base_model: mor40/BulBERT-chitanka-model
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -17,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # BulBERT-ner-bsnlp
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- This model is a fine-tuned version of [mor40/BulBERT-chitanka-model](https://huggingface.co/mor40/BulBERT-chitanka-model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1196
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- - Precision: 0.8460
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- - Recall: 0.8804
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- - F1: 0.8628
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- - Accuracy: 0.9680
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  ## Model description
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@@ -48,20 +48,27 @@ 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: 3
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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 | 91 | 0.1231 | 0.8234 | 0.8792 | 0.8504 | 0.9655 |
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- | No log | 2.0 | 182 | 0.1214 | 0.8296 | 0.8874 | 0.8576 | 0.9671 |
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- | No log | 3.0 | 273 | 0.1196 | 0.8460 | 0.8804 | 0.8628 | 0.9680 |
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.33.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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- - Tokenizers 0.13.3
 
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  ---
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+ base_model: mor40/BulBERT-ner-bsnlp
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # BulBERT-ner-bsnlp
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+ This model is a fine-tuned version of [mor40/BulBERT-ner-bsnlp](https://huggingface.co/mor40/BulBERT-ner-bsnlp) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1339
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+ - Precision: 0.8631
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+ - Recall: 0.9021
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+ - F1: 0.8822
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+ - Accuracy: 0.9716
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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 | 91 | 0.1240 | 0.8423 | 0.8882 | 0.8647 | 0.9681 |
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+ | No log | 2.0 | 182 | 0.1288 | 0.8281 | 0.8970 | 0.8612 | 0.9675 |
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+ | No log | 3.0 | 273 | 0.1205 | 0.8648 | 0.8936 | 0.8790 | 0.9706 |
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+ | No log | 4.0 | 364 | 0.1242 | 0.8635 | 0.8970 | 0.8799 | 0.9712 |
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+ | No log | 5.0 | 455 | 0.1249 | 0.8673 | 0.8908 | 0.8789 | 0.9711 |
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+ | 0.0469 | 6.0 | 546 | 0.1283 | 0.8597 | 0.8983 | 0.8786 | 0.9708 |
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+ | 0.0469 | 7.0 | 637 | 0.1316 | 0.8593 | 0.9018 | 0.8800 | 0.9710 |
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+ | 0.0469 | 8.0 | 728 | 0.1332 | 0.8622 | 0.9026 | 0.8819 | 0.9715 |
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+ | 0.0469 | 9.0 | 819 | 0.1330 | 0.8603 | 0.9023 | 0.8808 | 0.9714 |
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+ | 0.0469 | 10.0 | 910 | 0.1339 | 0.8631 | 0.9021 | 0.8822 | 0.9716 |
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  ### Framework versions
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+ - Transformers 4.34.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.5
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+ - Tokenizers 0.14.1