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Training complete

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README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  library_name: transformers
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- license: apache-2.0
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- base_model: bert-base-cased
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -26,16 +26,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.7806004618937644
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  - name: Recall
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  type: recall
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- value: 0.8589580686149937
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  - name: F1
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  type: f1
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- value: 0.8179068360556564
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  - name: Accuracy
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  type: accuracy
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- value: 0.9826963774430474
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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
@@ -43,13 +43,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-finetuned-ner
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- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0745
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- - Precision: 0.7806
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- - Recall: 0.8590
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- - F1: 0.8179
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- - Accuracy: 0.9827
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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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- | 0.1184 | 1.0 | 680 | 0.0607 | 0.7512 | 0.8285 | 0.7879 | 0.9823 |
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- | 0.044 | 2.0 | 1360 | 0.0616 | 0.7635 | 0.8450 | 0.8022 | 0.9832 |
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- | 0.0159 | 3.0 | 2040 | 0.0745 | 0.7806 | 0.8590 | 0.8179 | 0.9827 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ license: mit
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+ base_model: emilyalsentzer/Bio_ClinicalBERT
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8033573141486811
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  - name: Recall
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  type: recall
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+ value: 0.8513341804320204
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  - name: F1
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  type: f1
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+ value: 0.8266502159161011
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9835329804686291
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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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  # bert-finetuned-ner
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+ This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0626
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+ - Precision: 0.8034
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+ - Recall: 0.8513
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+ - F1: 0.8267
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+ - Accuracy: 0.9835
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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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+ | 0.1245 | 1.0 | 680 | 0.0536 | 0.7295 | 0.8158 | 0.7702 | 0.9814 |
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+ | 0.0392 | 2.0 | 1360 | 0.0551 | 0.7907 | 0.8399 | 0.8145 | 0.9831 |
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+ | 0.0155 | 3.0 | 2040 | 0.0626 | 0.8034 | 0.8513 | 0.8267 | 0.9835 |
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  ### Framework versions
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