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distilbert-base-uncased-finetuned-ner

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distilbert
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End of training

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  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
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: 0.438385803326849
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  - name: Recall
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  type: recall
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- value: 0.38719800834531365
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  - name: F1
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  type: f1
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- value: 0.4112050346317122
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  - name: Accuracy
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  type: accuracy
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- value: 0.6079383357712697
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the maccrobat_biomedical_ner dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6396
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- - Precision: 0.4384
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- - Recall: 0.3872
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- - F1: 0.4112
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- - Accuracy: 0.6079
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  ## Model description
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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 | 13 | 1.8288 | 0.3215 | 0.2593 | 0.2871 | 0.5356 |
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- | No log | 2.0 | 26 | 1.6907 | 0.3988 | 0.3448 | 0.3698 | 0.5838 |
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- | No log | 3.0 | 39 | 1.6396 | 0.4384 | 0.3872 | 0.4112 | 0.6079 |
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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: 0.0
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  - name: Recall
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  type: recall
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+ value: 0.0
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  - name: F1
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  type: f1
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+ value: 0.0
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  - name: Accuracy
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  type: accuracy
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+ value: 0.41848218895198763
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the maccrobat_biomedical_ner dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.4960
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+ - Precision: 0.0
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+ - Recall: 0.0
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+ - F1: 0.0
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+ - Accuracy: 0.4185
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  ## Model description
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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 | 10 | 2.9692 | 0.0 | 0.0 | 0.0 | 0.4185 |
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+ | No log | 2.0 | 20 | 2.5900 | 0.0 | 0.0 | 0.0 | 0.4185 |
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+ | No log | 3.0 | 30 | 2.4960 | 0.0 | 0.0 | 0.0 | 0.4185 |
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  ### Framework versions
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