Training complete

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0734
-- Precision: 0.7964
-- Recall: 0.7802
-- F1: 0.7882
-- Accuracy: 0.9771
+- Loss: 0.0739
+- Precision: 0.8048
+- Recall: 0.7953
+- F1: 0.8000
+- Accuracy: 0.9775
 
 ## Model description
 
@@ -50,20 +50,22 @@ 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  | 0.0866          | 0.7535    | 0.7694 | 0.7614 | 0.9741   |
-| No log        | 2.0   | 462  | 0.0734          | 0.7964    | 0.7802 | 0.7882 | 0.9771   |
+| No log        | 1.0   | 231  | 0.0877          | 0.7475    | 0.7719 | 0.7595 | 0.9733   |
+| No log        | 2.0   | 462  | 0.0766          | 0.7797    | 0.7900 | 0.7848 | 0.9756   |
+| 0.2598        | 3.0   | 693  | 0.0730          | 0.8042    | 0.7949 | 0.7995 | 0.9774   |
+| 0.2598        | 4.0   | 924  | 0.0739          | 0.8048    | 0.7953 | 0.8000 | 0.9775   |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.0+cu121
+- Pytorch 2.4.1+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1