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distilbert-base-uncased-finetuned-ner

Token Classification
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End of training

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Files changed (4) hide show
  1. README.md +9 -7
  2. logs/train/events.out.tfevents.1654570601.ea54c826b87f.73.0.v2 +2 -2
  3. logs/validation/events.out.tfevents.1654570706.ea54c826b87f.73.1.v2 +2 -2
  4. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,13 +14,13 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.1996
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- - Validation Loss: 0.0735
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- - Train Precision: 0.8930
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- - Train Recall: 0.9179
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- - Train F1: 0.9053
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- - Train Accuracy: 0.9784
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- - Epoch: 0
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  ## Model description
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@@ -47,6 +47,8 @@ The following hyperparameters were used during training:
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  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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  | 0.1996 | 0.0735 | 0.8930 | 0.9179 | 0.9053 | 0.9784 | 0 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.0339
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+ - Validation Loss: 0.0646
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+ - Train Precision: 0.9217
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+ - Train Recall: 0.9295
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+ - Train F1: 0.9256
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+ - Train Accuracy: 0.9827
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+ - Epoch: 2
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  ## Model description
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  | Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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  |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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  | 0.1996 | 0.0735 | 0.8930 | 0.9179 | 0.9053 | 0.9784 | 0 |
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+ | 0.0545 | 0.0666 | 0.9137 | 0.9292 | 0.9214 | 0.9817 | 1 |
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+ | 0.0339 | 0.0646 | 0.9217 | 0.9295 | 0.9256 | 0.9827 | 2 |
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  ### Framework versions
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