jialinselenasong
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biobert-finetuned-ner

Token Classification

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jialinselenasong commited on May 8

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4144
-- Precision: 0.6250
-- Recall: 0.6815
-- F1: 0.6520
-- Accuracy: 0.8601
 ## Model description
@@ -48,15 +48,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 305  | 0.4106          | 0.6036    | 0.6678 | 0.6340 | 0.8556   |
-| 0.4536        | 2.0   | 610  | 0.3975          | 0.6211    | 0.6825 | 0.6503 | 0.8601   |
-| 0.4536        | 3.0   | 915  | 0.4144          | 0.6250    | 0.6815 | 0.6520 | 0.8601   |
 ### Framework versions

 This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.6965
+- Precision: 0.6381
+- Recall: 0.6865
+- F1: 0.6614
+- Accuracy: 0.8583
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 305  | 0.4123          | 0.6110    | 0.6694 | 0.6389 | 0.8542   |
+| 0.4534        | 2.0   | 610  | 0.4023          | 0.6259    | 0.6848 | 0.6540 | 0.8586   |
+| 0.4534        | 3.0   | 915  | 0.4384          | 0.6369    | 0.6991 | 0.6666 | 0.8615   |
+| 0.2438        | 4.0   | 1220 | 0.4799          | 0.6445    | 0.6941 | 0.6684 | 0.8615   |
+| 0.1551        | 5.0   | 1525 | 0.5190          | 0.6464    | 0.6908 | 0.6678 | 0.8628   |
+| 0.1551        | 6.0   | 1830 | 0.5772          | 0.6454    | 0.6751 | 0.6599 | 0.8597   |
+| 0.1044        | 7.0   | 2135 | 0.6141          | 0.6413    | 0.6881 | 0.6639 | 0.8586   |
+| 0.1044        | 8.0   | 2440 | 0.6587          | 0.6353    | 0.6945 | 0.6636 | 0.8590   |
+| 0.0755        | 9.0   | 2745 | 0.6856          | 0.6357    | 0.6905 | 0.6620 | 0.8580   |
+| 0.0604        | 10.0  | 3050 | 0.6965          | 0.6381    | 0.6865 | 0.6614 | 0.8583   |
 ### Framework versions