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ytonthat
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drbert-7gb-finedtuned-ner

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  1. README.md +21 -19
  2. model.safetensors +1 -1
  3. runs/Mar01_14-35-57_6d7974edcc8d/events.out.tfevents.1709303758.6d7974edcc8d.7770.0 +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: 0.5151515151515151
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  - name: Recall
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  type: recall
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- value: 0.5749888740542947
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  - name: F1
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  type: f1
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- value: 0.5434279705573082
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  - name: Accuracy
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  type: accuracy
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- value: 0.8052467462039046
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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: 1.0979
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- - Precision: 0.5152
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- - Recall: 0.5750
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- - F1: 0.5434
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- - Accuracy: 0.8052
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  ## Model description
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@@ -67,26 +67,28 @@ 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: 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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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 8
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  ### Training results
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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 | 0.7366 | 0.4295 | 0.4815 | 0.4540 | 0.7706 |
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- | No log | 2.0 | 210 | 0.7073 | 0.4751 | 0.5256 | 0.4990 | 0.7844 |
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- | No log | 3.0 | 315 | 0.7970 | 0.5277 | 0.5087 | 0.5180 | 0.7960 |
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- | No log | 4.0 | 420 | 0.9072 | 0.4960 | 0.5287 | 0.5118 | 0.7926 |
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- | 0.4094 | 5.0 | 525 | 0.9859 | 0.4765 | 0.5696 | 0.5190 | 0.7899 |
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- | 0.4094 | 6.0 | 630 | 1.0399 | 0.5093 | 0.5750 | 0.5401 | 0.8039 |
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- | 0.4094 | 7.0 | 735 | 1.0778 | 0.5245 | 0.5723 | 0.5474 | 0.8065 |
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- | 0.4094 | 8.0 | 840 | 1.0979 | 0.5152 | 0.5750 | 0.5434 | 0.8052 |
 
 
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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: 0.502933124755573
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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
 
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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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  ### 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
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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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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