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bert-finetuned-ner

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bert
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  1. README.md +61 -61
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@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.5180180180180181
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  - name: Recall
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  type: recall
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- value: 0.31974050046339203
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  - name: F1
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  type: f1
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- value: 0.39541547277936967
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  - name: Accuracy
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  type: accuracy
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- value: 0.9357035175879397
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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
@@ -44,65 +44,65 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4235
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- - Precision: 0.5180
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- - Recall: 0.3197
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- - F1: 0.3954
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- - Accuracy: 0.9357
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- - Corporation Precision: 0.2222
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- - Corporation Recall: 0.2121
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- - Corporation F1: 0.2171
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- - Creative-work Precision: 0.4462
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- - Creative-work Recall: 0.2042
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- - Creative-work F1: 0.2802
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- - Group Precision: 0.4030
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- - Group Recall: 0.1636
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- - Group F1: 0.2328
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- - Location Precision: 0.5161
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  - Location Recall: 0.4267
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- - Location F1: 0.4672
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- - Person Precision: 0.7747
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  - Person Recall: 0.4569
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- - Person F1: 0.5748
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- - Product Precision: 0.1596
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  - Product Recall: 0.1181
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- - Product F1: 0.1357
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- - B-corporation Precision: 0.3696
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- - B-corporation Recall: 0.2576
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- - B-corporation F1: 0.3036
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- - B-creative-work Precision: 0.75
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- - B-creative-work Recall: 0.2535
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- - B-creative-work F1: 0.3789
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- - B-group Precision: 0.5
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- - B-group Recall: 0.1636
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- - B-group F1: 0.2466
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- - B-location Precision: 0.6293
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  - B-location Recall: 0.4867
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- - B-location F1: 0.5489
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- - B-person Precision: 0.8608
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- - B-person Recall: 0.4755
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- - B-person F1: 0.6126
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- - B-product Precision: 0.4545
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- - B-product Recall: 0.1969
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- - B-product F1: 0.2747
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- - I-corporation Precision: 0.3333
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  - I-corporation Recall: 0.2727
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- - I-corporation F1: 0.3
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- - I-creative-work Precision: 0.4262
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- - I-creative-work Recall: 0.2016
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- - I-creative-work F1: 0.2737
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- - I-group Precision: 0.3478
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- - I-group Recall: 0.1416
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- - I-group F1: 0.2013
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- - I-location Precision: 0.5932
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- - I-location Recall: 0.3684
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- - I-location F1: 0.4545
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- - I-person Precision: 0.7625
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  - I-person Recall: 0.3631
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- - I-person F1: 0.4919
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- - I-product Precision: 0.2222
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- - I-product Recall: 0.1488
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- - I-product F1: 0.1782
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  ## Model description
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@@ -133,14 +133,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Corporation Precision | Corporation Recall | Corporation F1 | Creative-work Precision | Creative-work Recall | Creative-work F1 | Group Precision | Group Recall | Group F1 | Location Precision | Location Recall | Location F1 | Person Precision | Person Recall | Person F1 | Product Precision | Product Recall | Product F1 | B-corporation Precision | B-corporation Recall | B-corporation F1 | B-creative-work Precision | B-creative-work Recall | B-creative-work F1 | B-group Precision | B-group Recall | B-group F1 | B-location Precision | B-location Recall | B-location F1 | B-person Precision | B-person Recall | B-person F1 | B-product Precision | B-product Recall | B-product F1 | I-corporation Precision | I-corporation Recall | I-corporation F1 | I-creative-work Precision | I-creative-work Recall | I-creative-work F1 | I-group Precision | I-group Recall | I-group F1 | I-location Precision | I-location Recall | I-location F1 | I-person Precision | I-person Recall | I-person F1 | I-product Precision | I-product Recall | I-product F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:---------------------:|:------------------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:----------------:|:-------------:|:---------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|
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- | No log | 1.0 | 425 | 0.3858 | 0.4406 | 0.2576 | 0.3251 | 0.9303 | 0.0741 | 0.0606 | 0.0667 | 0.0667 | 0.0141 | 0.0233 | 0.1458 | 0.0848 | 0.1073 | 0.3829 | 0.4467 | 0.4123 | 0.7235 | 0.4452 | 0.5512 | 0.0 | 0.0 | 0.0 | 0.2391 | 0.1667 | 0.1964 | 0.0 | 0.0 | 0.0 | 0.375 | 0.0909 | 0.1463 | 0.5137 | 0.5 | 0.5068 | 0.8675 | 0.4732 | 0.6124 | 0.0 | 0.0 | 0.0 | 0.1923 | 0.0909 | 0.1235 | 0.3 | 0.0698 | 0.1132 | 0.1447 | 0.0973 | 0.1164 | 0.3636 | 0.3789 | 0.3711 | 0.7184 | 0.3720 | 0.4902 | 0.0 | 0.0 | 0.0 |
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- | 0.199 | 2.0 | 850 | 0.4265 | 0.5295 | 0.2743 | 0.3614 | 0.9326 | 0.1444 | 0.1970 | 0.1667 | 0.4583 | 0.1549 | 0.2316 | 0.4483 | 0.0788 | 0.1340 | 0.5263 | 0.4 | 0.4545 | 0.7839 | 0.4312 | 0.5564 | 0.0714 | 0.0236 | 0.0355 | 0.2969 | 0.2879 | 0.2923 | 0.7297 | 0.1901 | 0.3017 | 0.7368 | 0.0848 | 0.1522 | 0.6635 | 0.46 | 0.5433 | 0.8981 | 0.4522 | 0.6016 | 0.5 | 0.0630 | 0.1119 | 0.2090 | 0.2545 | 0.2295 | 0.5581 | 0.1860 | 0.2791 | 0.3 | 0.0531 | 0.0902 | 0.5536 | 0.3263 | 0.4106 | 0.7619 | 0.3333 | 0.4638 | 0.1538 | 0.0496 | 0.075 |
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- | 0.0799 | 3.0 | 1275 | 0.4235 | 0.5180 | 0.3197 | 0.3954 | 0.9357 | 0.2222 | 0.2121 | 0.2171 | 0.4462 | 0.2042 | 0.2802 | 0.4030 | 0.1636 | 0.2328 | 0.5161 | 0.4267 | 0.4672 | 0.7747 | 0.4569 | 0.5748 | 0.1596 | 0.1181 | 0.1357 | 0.3696 | 0.2576 | 0.3036 | 0.75 | 0.2535 | 0.3789 | 0.5 | 0.1636 | 0.2466 | 0.6293 | 0.4867 | 0.5489 | 0.8608 | 0.4755 | 0.6126 | 0.4545 | 0.1969 | 0.2747 | 0.3333 | 0.2727 | 0.3 | 0.4262 | 0.2016 | 0.2737 | 0.3478 | 0.1416 | 0.2013 | 0.5932 | 0.3684 | 0.4545 | 0.7625 | 0.3631 | 0.4919 | 0.2222 | 0.1488 | 0.1782 |
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  ### Framework versions
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- - Transformers 4.34.1
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  - Pytorch 2.1.0+cu118
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  - Datasets 2.14.6
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  - Tokenizers 0.14.1
 
25
  metrics:
26
  - name: Precision
27
  type: precision
28
+ value: 0.5135542168674698
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  - name: Recall
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  type: recall
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+ value: 0.3160333642261353
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  - name: F1
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  type: f1
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+ value: 0.39127940332759614
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  - name: Accuracy
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  type: accuracy
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+ value: 0.936105527638191
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  ---
39
 
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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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45
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the wnut_17 dataset.
46
  It achieves the following results on the evaluation set:
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+ - Loss: 0.4228
48
+ - Precision: 0.5136
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+ - Recall: 0.3160
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+ - F1: 0.3913
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+ - Accuracy: 0.9361
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+ - Corporation Precision: 0.1746
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+ - Corporation Recall: 0.1667
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+ - Corporation F1: 0.1705
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+ - Creative-work Precision: 0.4286
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+ - Creative-work Recall: 0.2113
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+ - Creative-work F1: 0.2830
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+ - Group Precision: 0.3472
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+ - Group Recall: 0.1515
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+ - Group F1: 0.2110
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+ - Location Precision: 0.5378
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  - Location Recall: 0.4267
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+ - Location F1: 0.4758
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+ - Person Precision: 0.7778
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  - Person Recall: 0.4569
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+ - Person F1: 0.5756
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+ - Product Precision: 0.1705
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  - Product Recall: 0.1181
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+ - Product F1: 0.1395
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+ - B-corporation Precision: 0.2889
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+ - B-corporation Recall: 0.1970
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+ - B-corporation F1: 0.2342
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+ - B-creative-work Precision: 0.74
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+ - B-creative-work Recall: 0.2606
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+ - B-creative-work F1: 0.3854
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+ - B-group Precision: 0.4906
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+ - B-group Recall: 0.1576
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+ - B-group F1: 0.2385
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+ - B-location Precision: 0.6636
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  - B-location Recall: 0.4867
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+ - B-location F1: 0.5615
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+ - B-person Precision: 0.8523
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+ - B-person Recall: 0.4709
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+ - B-person F1: 0.6066
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+ - B-product Precision: 0.56
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+ - B-product Recall: 0.2205
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+ - B-product F1: 0.3164
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+ - I-corporation Precision: 0.3488
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  - I-corporation Recall: 0.2727
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+ - I-corporation F1: 0.3061
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+ - I-creative-work Precision: 0.4286
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+ - I-creative-work Recall: 0.2326
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+ - I-creative-work F1: 0.3015
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+ - I-group Precision: 0.2885
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+ - I-group Recall: 0.1327
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+ - I-group F1: 0.1818
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+ - I-location Precision: 0.5714
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+ - I-location Recall: 0.3789
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+ - I-location F1: 0.4557
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+ - I-person Precision: 0.8026
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  - I-person Recall: 0.3631
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+ - I-person F1: 0.5
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+ - I-product Precision: 0.2133
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+ - I-product Recall: 0.1322
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+ - I-product F1: 0.1633
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Corporation Precision | Corporation Recall | Corporation F1 | Creative-work Precision | Creative-work Recall | Creative-work F1 | Group Precision | Group Recall | Group F1 | Location Precision | Location Recall | Location F1 | Person Precision | Person Recall | Person F1 | Product Precision | Product Recall | Product F1 | B-corporation Precision | B-corporation Recall | B-corporation F1 | B-creative-work Precision | B-creative-work Recall | B-creative-work F1 | B-group Precision | B-group Recall | B-group F1 | B-location Precision | B-location Recall | B-location F1 | B-person Precision | B-person Recall | B-person F1 | B-product Precision | B-product Recall | B-product F1 | I-corporation Precision | I-corporation Recall | I-corporation F1 | I-creative-work Precision | I-creative-work Recall | I-creative-work F1 | I-group Precision | I-group Recall | I-group F1 | I-location Precision | I-location Recall | I-location F1 | I-person Precision | I-person Recall | I-person F1 | I-product Precision | I-product Recall | I-product F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:---------------------:|:------------------:|:--------------:|:-----------------------:|:--------------------:|:----------------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|:----------------:|:-------------:|:---------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|:-----------------------:|:--------------------:|:----------------:|:-------------------------:|:----------------------:|:------------------:|:-----------------:|:--------------:|:----------:|:--------------------:|:-----------------:|:-------------:|:------------------:|:---------------:|:-----------:|:-------------------:|:----------------:|:------------:|
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+ | No log | 1.0 | 425 | 0.3846 | 0.4564 | 0.2521 | 0.3248 | 0.9305 | 0.0 | 0.0 | 0.0 | 0.1522 | 0.0493 | 0.0745 | 0.1495 | 0.0970 | 0.1176 | 0.4370 | 0.3933 | 0.4140 | 0.7143 | 0.4429 | 0.5468 | 0.0 | 0.0 | 0.0 | 0.2414 | 0.1061 | 0.1474 | 0.0 | 0.0 | 0.0 | 0.2632 | 0.0909 | 0.1351 | 0.6075 | 0.4333 | 0.5058 | 0.8694 | 0.4499 | 0.5929 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3261 | 0.1163 | 0.1714 | 0.1486 | 0.0973 | 0.1176 | 0.3882 | 0.3474 | 0.3667 | 0.7160 | 0.3601 | 0.4792 | 0.1818 | 0.0165 | 0.0303 |
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+ | 0.202 | 2.0 | 850 | 0.4309 | 0.5463 | 0.2734 | 0.3644 | 0.9325 | 0.1831 | 0.1970 | 0.1898 | 0.5116 | 0.1549 | 0.2378 | 0.3889 | 0.0848 | 0.1393 | 0.5354 | 0.3533 | 0.4257 | 0.7924 | 0.4359 | 0.5624 | 0.1091 | 0.0472 | 0.0659 | 0.2586 | 0.2273 | 0.2419 | 0.8065 | 0.1761 | 0.2890 | 0.5556 | 0.0909 | 0.1562 | 0.6897 | 0.4 | 0.5063 | 0.8784 | 0.4545 | 0.5991 | 0.6364 | 0.1102 | 0.1879 | 0.35 | 0.2545 | 0.2947 | 0.6 | 0.1860 | 0.2840 | 0.375 | 0.0796 | 0.1314 | 0.5882 | 0.3158 | 0.4110 | 0.7872 | 0.3304 | 0.4654 | 0.1429 | 0.0579 | 0.0824 |
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+ | 0.0826 | 3.0 | 1275 | 0.4228 | 0.5136 | 0.3160 | 0.3913 | 0.9361 | 0.1746 | 0.1667 | 0.1705 | 0.4286 | 0.2113 | 0.2830 | 0.3472 | 0.1515 | 0.2110 | 0.5378 | 0.4267 | 0.4758 | 0.7778 | 0.4569 | 0.5756 | 0.1705 | 0.1181 | 0.1395 | 0.2889 | 0.1970 | 0.2342 | 0.74 | 0.2606 | 0.3854 | 0.4906 | 0.1576 | 0.2385 | 0.6636 | 0.4867 | 0.5615 | 0.8523 | 0.4709 | 0.6066 | 0.56 | 0.2205 | 0.3164 | 0.3488 | 0.2727 | 0.3061 | 0.4286 | 0.2326 | 0.3015 | 0.2885 | 0.1327 | 0.1818 | 0.5714 | 0.3789 | 0.4557 | 0.8026 | 0.3631 | 0.5 | 0.2133 | 0.1322 | 0.1633 |
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  ### Framework versions
142
 
143
+ - Transformers 4.35.0
144
  - Pytorch 2.1.0+cu118
145
  - Datasets 2.14.6
146
  - Tokenizers 0.14.1