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ytonthat
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drbert-7gb-finedtuned-ner

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  1. README.md +17 -17
  2. model.safetensors +1 -1
  3. runs/Mar01_03-20-24_1cc23fee8ba3/events.out.tfevents.1709263225.1cc23fee8ba3.4565.4 +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: 0.7244534824605999
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  - name: Recall
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  type: recall
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- value: 0.7437369519832986
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  - name: F1
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  type: f1
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- value: 0.7339685809940767
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  - name: Accuracy
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  type: accuracy
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- value: 0.9228702993092862
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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: 0.4365
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- - Precision: 0.7245
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- - Recall: 0.7437
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- - F1: 0.7340
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- - Accuracy: 0.9229
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  ## Model description
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@@ -79,14 +79,14 @@ 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 | 61 | 0.4138 | 0.7069 | 0.7035 | 0.7052 | 0.9185 |
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- | No log | 2.0 | 122 | 0.3855 | 0.6853 | 0.7307 | 0.7072 | 0.9153 |
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- | No log | 3.0 | 183 | 0.4027 | 0.6563 | 0.7526 | 0.7012 | 0.9141 |
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- | No log | 4.0 | 244 | 0.4251 | 0.6692 | 0.7390 | 0.7024 | 0.9165 |
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- | No log | 5.0 | 305 | 0.4165 | 0.7099 | 0.7432 | 0.7262 | 0.9211 |
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- | No log | 6.0 | 366 | 0.4493 | 0.7339 | 0.7213 | 0.7276 | 0.9211 |
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- | No log | 7.0 | 427 | 0.4324 | 0.7169 | 0.7443 | 0.7303 | 0.9228 |
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- | No log | 8.0 | 488 | 0.4365 | 0.7245 | 0.7437 | 0.7340 | 0.9229 |
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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: 0.7396149949341438
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  - name: Recall
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  type: recall
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+ value: 0.7620041753653445
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  - name: F1
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  type: f1
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+ value: 0.7506426735218509
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9288181120491175
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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: 0.3751
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+ - Precision: 0.7396
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+ - Recall: 0.7620
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+ - F1: 0.7506
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+ - Accuracy: 0.9288
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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 | 61 | 0.3631 | 0.6608 | 0.6221 | 0.6409 | 0.9048 |
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+ | No log | 2.0 | 122 | 0.3148 | 0.7103 | 0.6707 | 0.6899 | 0.9146 |
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+ | No log | 3.0 | 183 | 0.3269 | 0.7092 | 0.7651 | 0.7361 | 0.9239 |
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+ | No log | 4.0 | 244 | 0.3190 | 0.7190 | 0.7677 | 0.7426 | 0.9259 |
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+ | No log | 5.0 | 305 | 0.3660 | 0.7114 | 0.7270 | 0.7192 | 0.9236 |
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+ | No log | 6.0 | 366 | 0.3683 | 0.7361 | 0.7542 | 0.7450 | 0.9273 |
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+ | No log | 7.0 | 427 | 0.3724 | 0.7448 | 0.7599 | 0.7523 | 0.9289 |
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+ | No log | 8.0 | 488 | 0.3751 | 0.7396 | 0.7620 | 0.7506 | 0.9288 |
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  ### Framework versions
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