GuCuChiara
/

NLP-HIBA_BiomedNLP-BiomedBERT-base-pretrained-model

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1766
-- Precision: 0.5977
-- Recall: 0.5730
-- F1: 0.5851
-- Accuracy: 0.9539
 ## Model description
@@ -49,22 +49,24 @@ 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: 10
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 71   | 0.1981          | 0.2581    | 0.2239 | 0.2398 | 0.9266   |
-| No log        | 2.0   | 142  | 0.1616          | 0.4514    | 0.3692 | 0.4062 | 0.9444   |
-| No log        | 3.0   | 213  | 0.1514          | 0.5233    | 0.4727 | 0.4967 | 0.9482   |
-| No log        | 4.0   | 284  | 0.1863          | 0.4522    | 0.5546 | 0.4982 | 0.9352   |
-| No log        | 5.0   | 355  | 0.1582          | 0.5665    | 0.5245 | 0.5447 | 0.9498   |
-| No log        | 6.0   | 426  | 0.1571          | 0.5915    | 0.5305 | 0.5593 | 0.9529   |
-| No log        | 7.0   | 497  | 0.1652          | 0.5849    | 0.5586 | 0.5714 | 0.9527   |
-| 0.1311        | 8.0   | 568  | 0.1676          | 0.5858    | 0.5738 | 0.5798 | 0.9528   |
-| 0.1311        | 9.0   | 639  | 0.1748          | 0.5990    | 0.5562 | 0.5768 | 0.9537   |
-| 0.1311        | 10.0  | 710  | 0.1766          | 0.5977    | 0.5730 | 0.5851 | 0.9539   |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.2050
+- Precision: 0.6079
+- Recall: 0.5407
+- F1: 0.5723
+- Accuracy: 0.9528
 ## Model description
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- num_epochs: 12
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 71   | 0.2223          | 0.3125    | 0.1619 | 0.2133 | 0.9212   |
+| No log        | 2.0   | 142  | 0.1599          | 0.5228    | 0.3539 | 0.4221 | 0.9446   |
+| No log        | 3.0   | 213  | 0.1472          | 0.5298    | 0.4385 | 0.4798 | 0.9470   |
+| No log        | 4.0   | 284  | 0.1441          | 0.5885    | 0.4729 | 0.5244 | 0.9514   |
+| No log        | 5.0   | 355  | 0.1675          | 0.5654    | 0.5146 | 0.5388 | 0.9491   |
+| No log        | 6.0   | 426  | 0.1592          | 0.5860    | 0.5082 | 0.5443 | 0.9521   |
+| No log        | 7.0   | 497  | 0.1634          | 0.5621    | 0.5587 | 0.5604 | 0.9509   |
+| 0.1349        | 8.0   | 568  | 0.1897          | 0.5803    | 0.5182 | 0.5475 | 0.9515   |
+| 0.1349        | 9.0   | 639  | 0.1880          | 0.5699    | 0.5539 | 0.5618 | 0.9506   |
+| 0.1349        | 10.0  | 710  | 0.1939          | 0.5923    | 0.5415 | 0.5657 | 0.9525   |
+| 0.1349        | 11.0  | 781  | 0.1988          | 0.5863    | 0.5475 | 0.5662 | 0.9518   |
+| 0.1349        | 12.0  | 852  | 0.2050          | 0.6079    | 0.5407 | 0.5723 | 0.9528   |
 ### Framework versions