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: 0.0780
-- Precision: 0.8002
-- Recall: 0.7735
-- F1: 0.7866
-- Accuracy: 0.9772
+- Loss: 0.0712
+- Precision: 0.8087
+- Recall: 0.7954
+- F1: 0.8020
+- Accuracy: 0.9781
 
 ## Model description
 
@@ -51,20 +51,22 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 2
+- num_epochs: 4
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 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   |
+| No log        | 1.0   | 231  | 0.0934          | 0.7464    | 0.7652 | 0.7557 | 0.9730   |
+| No log        | 2.0   | 462  | 0.0730          | 0.7975    | 0.7915 | 0.7945 | 0.9774   |
+| 0.2789        | 3.0   | 693  | 0.0713          | 0.8075    | 0.7924 | 0.7999 | 0.9777   |
+| 0.2789        | 4.0   | 924  | 0.0712          | 0.8087    | 0.7954 | 0.8020 | 0.9781   |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.0+cu121
+- Pytorch 2.4.1+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1