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Catastrophic Forgetting Fixed

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  1. README.md +8 -8
README.md CHANGED
@@ -1,5 +1,6 @@
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -7,7 +8,6 @@ metrics:
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  - recall
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  - f1
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  - accuracy
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- base_model: dslim/bert-large-NER
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  model-index:
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  - name: bert-finetuned-ner-adam
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  results: []
@@ -21,10 +21,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dslim/bert-large-NER](https://huggingface.co/dslim/bert-large-NER) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: nan
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- - Precision: 0.8340
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- - Recall: 0.8131
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- - F1: 0.8234
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- - Accuracy: 0.9216
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  ## Model description
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@@ -55,9 +55,9 @@ 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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- | 0.1744 | 1.0 | 893 | nan | 0.8276 | 0.8115 | 0.8195 | 0.9205 |
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- | 0.128 | 2.0 | 1786 | nan | 0.8404 | 0.8256 | 0.8329 | 0.9238 |
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- | 0.0768 | 3.0 | 2679 | nan | 0.8340 | 0.8131 | 0.8234 | 0.9216 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: dslim/bert-large-NER
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  - recall
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  - f1
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  - accuracy
 
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  model-index:
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  - name: bert-finetuned-ner-adam
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  results: []
 
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  This model is a fine-tuned version of [dslim/bert-large-NER](https://huggingface.co/dslim/bert-large-NER) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: nan
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+ - Precision: 0.8845
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+ - Recall: 0.8749
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+ - F1: 0.8797
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+ - Accuracy: 0.9646
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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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+ | 0.0949 | 1.0 | 3080 | nan | 0.8914 | 0.8942 | 0.8928 | 0.9663 |
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+ | 0.0574 | 2.0 | 6160 | nan | 0.8763 | 0.8784 | 0.8773 | 0.9635 |
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+ | 0.0376 | 3.0 | 9240 | nan | 0.8845 | 0.8749 | 0.8797 | 0.9646 |
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  ### Framework versions