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ytonthat
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drbert-7gb-finedtuned-ner

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  1. README.md +19 -19
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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: 0.5105965463108321
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  - name: Recall
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  type: recall
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- value: 0.5789942145082332
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  - name: F1
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  type: f1
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- value: 0.5426485922836287
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  - name: Accuracy
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  type: accuracy
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- value: 0.8011795010845987
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Dr-BERT/DrBERT-7GB](https://huggingface.co/Dr-BERT/DrBERT-7GB) on the quaero dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2226
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- - Precision: 0.5106
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- - Recall: 0.5790
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- - F1: 0.5426
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- - Accuracy: 0.8012
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  ## Model description
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@@ -79,16 +79,16 @@ 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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- | No log | 1.0 | 105 | 0.7160 | 0.4596 | 0.4713 | 0.4654 | 0.7764 |
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- | No log | 2.0 | 210 | 0.6985 | 0.4484 | 0.5220 | 0.4824 | 0.7831 |
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- | No log | 3.0 | 315 | 0.8448 | 0.4872 | 0.5234 | 0.5046 | 0.7881 |
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- | No log | 4.0 | 420 | 0.9029 | 0.5231 | 0.5403 | 0.5315 | 0.8017 |
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- | 0.4116 | 5.0 | 525 | 1.0169 | 0.4813 | 0.5656 | 0.5200 | 0.7892 |
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- | 0.4116 | 6.0 | 630 | 1.0596 | 0.5150 | 0.5665 | 0.5395 | 0.7986 |
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- | 0.4116 | 7.0 | 735 | 1.1298 | 0.4954 | 0.5705 | 0.5303 | 0.8000 |
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- | 0.4116 | 8.0 | 840 | 1.1665 | 0.4949 | 0.5803 | 0.5342 | 0.7984 |
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- | 0.4116 | 9.0 | 945 | 1.2045 | 0.5135 | 0.5754 | 0.5427 | 0.8025 |
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- | 0.0254 | 10.0 | 1050 | 1.2226 | 0.5106 | 0.5790 | 0.5426 | 0.8012 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.5055292259083728
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  - name: Recall
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  type: recall
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+ value: 0.5696484201157098
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  - name: F1
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  type: f1
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+ value: 0.5356769198577107
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8004338394793926
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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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  This model is a fine-tuned version of [Dr-BERT/DrBERT-7GB](https://huggingface.co/Dr-BERT/DrBERT-7GB) on the quaero dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2330
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+ - Precision: 0.5055
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+ - Recall: 0.5696
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+ - F1: 0.5357
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+ - Accuracy: 0.8004
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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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+ | No log | 1.0 | 105 | 0.7430 | 0.4129 | 0.4775 | 0.4428 | 0.7671 |
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+ | No log | 2.0 | 210 | 0.6968 | 0.4888 | 0.5042 | 0.4964 | 0.7888 |
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+ | No log | 3.0 | 315 | 0.8218 | 0.5059 | 0.5323 | 0.5188 | 0.7952 |
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+ | No log | 4.0 | 420 | 0.9307 | 0.4869 | 0.5563 | 0.5193 | 0.7913 |
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+ | 0.4134 | 5.0 | 525 | 0.9970 | 0.4688 | 0.5581 | 0.5095 | 0.7870 |
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+ | 0.4134 | 6.0 | 630 | 1.0503 | 0.4992 | 0.5541 | 0.5252 | 0.7930 |
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+ | 0.4134 | 7.0 | 735 | 1.1364 | 0.5034 | 0.5607 | 0.5305 | 0.7994 |
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+ | 0.4134 | 8.0 | 840 | 1.1994 | 0.4865 | 0.5701 | 0.5250 | 0.7937 |
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+ | 0.4134 | 9.0 | 945 | 1.2287 | 0.4948 | 0.5683 | 0.5290 | 0.7982 |
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+ | 0.028 | 10.0 | 1050 | 1.2330 | 0.5055 | 0.5696 | 0.5357 | 0.8004 |
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  ### Framework versions