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ytonthat
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drbert-7gb-finedtuned-ner

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  1. README.md +20 -20
  2. model.safetensors +1 -1
  3. runs/Mar01_14-43-30_6d7974edcc8d/events.out.tfevents.1709304211.6d7974edcc8d.9840.0 +2 -2
README.md CHANGED
@@ -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: 0.502933124755573
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  - name: Recall
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  type: recall
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- value: 0.5723186470850022
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  - name: F1
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  type: f1
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- value: 0.5353871773522064
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  - name: Accuracy
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  type: accuracy
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- value: 0.7962988069414316
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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: 1.2469
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- - Precision: 0.5029
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- - Recall: 0.5723
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- - F1: 0.5354
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- - Accuracy: 0.7963
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  ## Model description
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@@ -67,7 +67,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -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 | 0.7546 | 0.4019 | 0.4766 | 0.4361 | 0.7598 |
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- | No log | 2.0 | 210 | 0.7426 | 0.4483 | 0.4980 | 0.4719 | 0.7785 |
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- | No log | 3.0 | 315 | 0.8678 | 0.4413 | 0.5349 | 0.4836 | 0.7694 |
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- | No log | 4.0 | 420 | 0.9466 | 0.4484 | 0.5336 | 0.4873 | 0.7780 |
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- | 0.4639 | 5.0 | 525 | 1.0138 | 0.4767 | 0.5194 | 0.4971 | 0.7864 |
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- | 0.4639 | 6.0 | 630 | 1.0300 | 0.4831 | 0.5269 | 0.5040 | 0.7820 |
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- | 0.4639 | 7.0 | 735 | 1.1711 | 0.4841 | 0.5572 | 0.5181 | 0.7855 |
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- | 0.4639 | 8.0 | 840 | 1.1943 | 0.5117 | 0.5434 | 0.5271 | 0.7960 |
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- | 0.4639 | 9.0 | 945 | 1.2376 | 0.5115 | 0.5719 | 0.5400 | 0.7955 |
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- | 0.0379 | 10.0 | 1050 | 1.2469 | 0.5029 | 0.5723 | 0.5354 | 0.7963 |
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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: 0.5186372745490982
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  - name: Recall
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  type: recall
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+ value: 0.5758789497107254
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  - name: F1
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  type: f1
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+ value: 0.5457612821594264
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8037554229934925
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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: 1.2062
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+ - Precision: 0.5186
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+ - Recall: 0.5759
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+ - F1: 0.5458
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+ - Accuracy: 0.8038
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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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 | 0.7393 | 0.4462 | 0.4775 | 0.4613 | 0.7751 |
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+ | No log | 2.0 | 210 | 0.7016 | 0.4637 | 0.5265 | 0.4931 | 0.7845 |
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+ | No log | 3.0 | 315 | 0.8441 | 0.4777 | 0.5109 | 0.4938 | 0.7849 |
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+ | No log | 4.0 | 420 | 0.9610 | 0.4857 | 0.5456 | 0.5139 | 0.7903 |
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+ | 0.4073 | 5.0 | 525 | 1.0035 | 0.4788 | 0.5688 | 0.5199 | 0.7884 |
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+ | 0.4073 | 6.0 | 630 | 1.0399 | 0.4872 | 0.5745 | 0.5273 | 0.7970 |
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+ | 0.4073 | 7.0 | 735 | 1.1211 | 0.4868 | 0.5665 | 0.5237 | 0.7913 |
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+ | 0.4073 | 8.0 | 840 | 1.1545 | 0.5124 | 0.5688 | 0.5391 | 0.8054 |
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+ | 0.4073 | 9.0 | 945 | 1.2049 | 0.4973 | 0.5728 | 0.5324 | 0.7984 |
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+ | 0.0272 | 10.0 | 1050 | 1.2062 | 0.5186 | 0.5759 | 0.5458 | 0.8038 |
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  ### Framework versions
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