Training complete

README.md

@@ -21,11 +21,11 @@ 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: 0.0633
-- Precision: 0.8475
-- Recall: 0.8335
-- F1: 0.8404
-- Accuracy: 0.9812
+- Loss: 0.0780
+- Precision: 0.8002
+- Recall: 0.7735
+- F1: 0.7866
+- Accuracy: 0.9772
 
 ## Model description
 
@@ -58,13 +58,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 231  | 0.0845          | 0.7793    | 0.8007 | 0.7898 | 0.9758   |
-| No log        | 2.0   | 462  | 0.0633          | 0.8475    | 0.8335 | 0.8404 | 0.9812   |
+| No log        | 1.0   | 231  | 0.0932          | 0.7529    | 0.7616 | 0.7572 | 0.9734   |
+| No log        | 2.0   | 462  | 0.0780          | 0.8002    | 0.7735 | 0.7866 | 0.9772   |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.1+cu121
+- Pytorch 2.4.0+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1

runs/Sep05_15-01-08_dc810888a375/events.out.tfevents.1725548469.dc810888a375.3692.4

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+size 7059