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SourceData_GeneprodRoles_v1_0_0_BioLinkBERT_large

Token Classification
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Safetensors
bert
Generated from Trainer
Eval Results (legacy)
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  1. README.md +9 -9
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@@ -25,13 +25,13 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9232191099104223
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  - name: Recall
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  type: recall
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- value: 0.9291199618411639
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  - name: F1
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  type: f1
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- value: 0.9261601369341955
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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
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the source_data dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0130
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- - Accuracy Score: 0.9950
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- - Precision: 0.9232
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- - Recall: 0.9291
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- - F1: 0.9262
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
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- | 0.0145 | 0.9994 | 863 | 0.0130 | 0.9950 | 0.9232 | 0.9291 | 0.9262 |
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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: 0.9233319126769901
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  - name: Recall
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  type: recall
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+ value: 0.9300262341998569
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  - name: F1
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  type: f1
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+ value: 0.9266669835083884
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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 [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the source_data dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0123
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+ - Accuracy Score: 0.9951
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+ - Precision: 0.9233
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+ - Recall: 0.9300
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+ - F1: 0.9267
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
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+ | 0.0138 | 0.9994 | 863 | 0.0123 | 0.9951 | 0.9233 | 0.9300 | 0.9267 |
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  ### Framework versions