NHS-pubmedbert-binary-random

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7488
-- Accuracy: 0.8044
-- Precision: 0.8023
-- Recall: 0.7949
-- F1: 0.7977
+- Loss: 0.5861
+- Accuracy: 0.8246
+- Precision: 0.8180
+- Recall: 0.8240
+- F1: 0.8202
 
 ## Model description
 
@@ -55,9 +55,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
-| 0.0153        | 1.0   | 397  | 0.4645          | 0.8120   | 0.8215    | 0.7944 | 0.8008 |
-| 0.0499        | 2.0   | 794  | 0.5122          | 0.8164   | 0.8157    | 0.8063 | 0.8097 |
-| 0.0059        | 3.0   | 1191 | 0.7488          | 0.8044   | 0.8023    | 0.7949 | 0.7977 |
+| 0.0592        | 1.0   | 397  | 0.3980          | 0.8246   | 0.8179    | 0.8220 | 0.8196 |
+| 0.0542        | 2.0   | 794  | 0.4714          | 0.7943   | 0.7960    | 0.8064 | 0.7929 |
+| 0.6307        | 3.0   | 1191 | 0.5861          | 0.8246   | 0.8180    | 0.8240 | 0.8202 |
 
 
 ### Framework versions

model.safetensors

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runs/Mar26_05-36-15_d4944df8337e/events.out.tfevents.1711431376.d4944df8337e.190.0

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