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End of training

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  1. README.md +14 -14
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: distilbert/distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -26,16 +26,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8894709271870089
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  - name: Recall
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  type: recall
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- value: 0.9019121813031161
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  - name: F1
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  type: f1
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- value: 0.8956483516483517
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  - name: Accuracy
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  type: accuracy
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- value: 0.9791105846882739
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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
@@ -43,13 +43,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # ner_model_2
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- This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1156
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- - Precision: 0.8895
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- - Recall: 0.9019
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- - F1: 0.8956
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- - Accuracy: 0.9791
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  ## Model description
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@@ -80,9 +80,9 @@ 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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- | 0.207 | 1.0 | 878 | 0.1029 | 0.8715 | 0.8862 | 0.8788 | 0.9756 |
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- | 0.0398 | 2.0 | 1756 | 0.1129 | 0.8753 | 0.9019 | 0.8884 | 0.9777 |
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- | 0.0223 | 3.0 | 2634 | 0.1156 | 0.8895 | 0.9019 | 0.8956 | 0.9791 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: distilbert/distilbert-base-cased
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8793253347243958
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  - name: Recall
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  type: recall
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+ value: 0.8953611898016998
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  - name: F1
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  type: f1
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+ value: 0.8872708132292307
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9776031011090772
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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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  # ner_model_2
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+ This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1230
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+ - Precision: 0.8793
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+ - Recall: 0.8954
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+ - F1: 0.8873
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+ - Accuracy: 0.9776
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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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+ | 0.1882 | 1.0 | 878 | 0.1169 | 0.8557 | 0.8798 | 0.8676 | 0.9744 |
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+ | 0.0376 | 2.0 | 1756 | 0.1160 | 0.8811 | 0.8962 | 0.8886 | 0.9779 |
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+ | 0.0202 | 3.0 | 2634 | 0.1230 | 0.8793 | 0.8954 | 0.8873 | 0.9776 |
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  ### Framework versions
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