Model save

README.md

@@ -1,6 +1,6 @@
 ---
-license: apache-2.0
-base_model: michiyasunaga/BioLinkBERT-base
+license: mit
+base_model: emilyalsentzer/Bio_ClinicalBERT
 tags:
 - generated_from_trainer
 datasets:
@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.62
+      value: 0.6
     - name: Precision
       type: precision
-      value: 0.6273344651952462
+      value: 0.6000400160064026
     - name: Recall
       type: recall
-      value: 0.62
+      value: 0.6
     - name: F1
       type: f1
-      value: 0.614448051948052
+      value: 0.5999599959995999
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # run1
 
-This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the sem_eval_2024_task_2 dataset.
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the sem_eval_2024_task_2 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6923
-- Accuracy: 0.62
-- Precision: 0.6273
-- Recall: 0.62
-- F1: 0.6144
+- Loss: 0.6634
+- Accuracy: 0.6
+- Precision: 0.6000
+- Recall: 0.6
+- F1: 0.6000
 
 ## Model description
 
@@ -82,16 +82,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| No log        | 0.99  | 53   | 0.6893          | 0.55     | 0.5565    | 0.55   | 0.5366 |
-| 0.7034        | 2.0   | 107  | 0.6771          | 0.595    | 0.5986    | 0.595  | 0.5913 |
-| 0.7034        | 2.99  | 160  | 0.6680          | 0.585    | 0.5882    | 0.585  | 0.5812 |
-| 0.6769        | 4.0   | 214  | 0.6448          | 0.625    | 0.6271    | 0.625  | 0.6234 |
-| 0.6769        | 4.99  | 267  | 0.6465          | 0.625    | 0.6503    | 0.625  | 0.6085 |
-| 0.5962        | 6.0   | 321  | 0.6457          | 0.635    | 0.6456    | 0.635  | 0.6282 |
-| 0.5962        | 6.99  | 374  | 0.6595          | 0.63     | 0.6366    | 0.63   | 0.6255 |
-| 0.4977        | 8.0   | 428  | 0.6763          | 0.62     | 0.6273    | 0.62   | 0.6144 |
-| 0.4977        | 8.99  | 481  | 0.6831          | 0.63     | 0.6379    | 0.63   | 0.6246 |
-| 0.4268        | 9.91  | 530  | 0.6923          | 0.62     | 0.6273    | 0.62   | 0.6144 |
+| No log        | 0.99  | 53   | 0.6935          | 0.515    | 0.5177    | 0.515  | 0.4958 |
+| 0.7014        | 2.0   | 107  | 0.6895          | 0.535    | 0.5363    | 0.535  | 0.5308 |
+| 0.7014        | 2.99  | 160  | 0.6894          | 0.52     | 0.5267    | 0.52   | 0.488  |
+| 0.6961        | 4.0   | 214  | 0.6846          | 0.575    | 0.5842    | 0.575  | 0.5631 |
+| 0.6961        | 4.99  | 267  | 0.6837          | 0.535    | 0.5931    | 0.535  | 0.4490 |
+| 0.687         | 6.0   | 321  | 0.6762          | 0.585    | 0.5852    | 0.585  | 0.5847 |
+| 0.687         | 6.99  | 374  | 0.6738          | 0.58     | 0.58      | 0.58   | 0.58   |
+| 0.6707        | 8.0   | 428  | 0.6677          | 0.59     | 0.5900    | 0.59   | 0.5900 |
+| 0.6707        | 8.99  | 481  | 0.6670          | 0.575    | 0.5767    | 0.575  | 0.5726 |
+| 0.653         | 9.91  | 530  | 0.6634          | 0.6      | 0.6000    | 0.6    | 0.6000 |
 
 
 ### Framework versions