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bert-base-NER-finetuned-ner-cerec

Token Classification
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PyTorch
bert
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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2862
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- - Precision: 0.8235
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- - Recall: 0.6853
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- - F1: 0.7481
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- - Accuracy: 0.9517
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  ## Model description
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@@ -48,15 +48,22 @@ 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: 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 | 45 | 0.5671 | 0.6 | 0.5455 | 0.5714 | 0.9167 |
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- | No log | 2.0 | 90 | 0.3043 | 0.7667 | 0.6434 | 0.6996 | 0.9447 |
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- | No log | 3.0 | 135 | 0.2862 | 0.8235 | 0.6853 | 0.7481 | 0.9517 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1511
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+ - Precision: 0.8652
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+ - Recall: 0.8531
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+ - F1: 0.8592
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+ - Accuracy: 0.9790
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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 | 45 | 0.4929 | 0.6532 | 0.5664 | 0.6067 | 0.9237 |
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+ | No log | 2.0 | 90 | 0.3090 | 0.8145 | 0.7063 | 0.7566 | 0.9497 |
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+ | No log | 3.0 | 135 | 0.2477 | 0.8433 | 0.7902 | 0.8159 | 0.9625 |
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+ | No log | 4.0 | 180 | 0.2209 | 0.8169 | 0.8112 | 0.8140 | 0.9669 |
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+ | No log | 5.0 | 225 | 0.1906 | 0.8369 | 0.8252 | 0.8310 | 0.9739 |
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+ | No log | 6.0 | 270 | 0.1568 | 0.8662 | 0.8601 | 0.8632 | 0.9784 |
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+ | No log | 7.0 | 315 | 0.1532 | 0.8732 | 0.8671 | 0.8702 | 0.9790 |
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+ | No log | 8.0 | 360 | 0.1530 | 0.8671 | 0.8671 | 0.8671 | 0.9790 |
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+ | No log | 9.0 | 405 | 0.1526 | 0.8723 | 0.8601 | 0.8662 | 0.9790 |
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+ | No log | 10.0 | 450 | 0.1511 | 0.8652 | 0.8531 | 0.8592 | 0.9790 |
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  ### Framework versions