Brizape
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SETH_5e-05_0404_ES6_strict_tok

Token Classification

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Brizape commited on Apr 6, 2023

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update model card README.md

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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 [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0952
-- Precision: 0.7390
-- Recall: 0.7504
-- F1: 0.7447
-- Accuracy: 0.9701
 ## Model description
@@ -54,13 +54,13 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.5183        | 0.96  | 25   | 0.2791          | 0.0       | 0.0    | 0.0    | 0.9291   |
-| 0.1921        | 1.92  | 50   | 0.1466          | 0.5556    | 0.0430 | 0.0799 | 0.9310   |
-| 0.1093        | 2.88  | 75   | 0.0965          | 0.7052    | 0.5559 | 0.6218 | 0.9638   |
-| 0.073         | 3.85  | 100  | 0.0931          | 0.6361    | 0.8485 | 0.7271 | 0.9625   |
-| 0.0605        | 4.81  | 125  | 0.0812          | 0.7513    | 0.7539 | 0.7526 | 0.9693   |
-| 0.0397        | 5.77  | 150  | 0.0967          | 0.6809    | 0.7126 | 0.6964 | 0.9685   |
-| 0.0339        | 6.73  | 175  | 0.0952          | 0.7390    | 0.7504 | 0.7447 | 0.9701   |
 ### Framework versions

 This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.0824
+- Precision: 0.7891
+- Recall: 0.7470
+- F1: 0.7675
+- Accuracy: 0.9741
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.4311        | 0.96  | 25   | 0.1785          | 0.7       | 0.0120 | 0.0237 | 0.9354   |
+| 0.1235        | 1.92  | 50   | 0.0961          | 0.6732    | 0.7091 | 0.6907 | 0.9655   |
+| 0.0749        | 2.88  | 75   | 0.0858          | 0.6801    | 0.8417 | 0.7523 | 0.9692   |
+| 0.063         | 3.85  | 100  | 0.0857          | 0.6764    | 0.8744 | 0.7628 | 0.9666   |
+| 0.0521        | 4.81  | 125  | 0.0757          | 0.7419    | 0.7522 | 0.7470 | 0.9723   |
+| 0.0336        | 5.77  | 150  | 0.0829          | 0.7170    | 0.7935 | 0.7533 | 0.9714   |
+| 0.0287        | 6.73  | 175  | 0.0824          | 0.7891    | 0.7470 | 0.7675 | 0.9741   |
 ### Framework versions