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 [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0849
-- Precision: 0.7712
-- Recall: 0.7700
-- F1: 0.7706
-- Accuracy: 0.9738
+- Loss: 0.0834
+- Precision: 0.7938
+- Recall: 0.7935
+- F1: 0.7936
+- Accuracy: 0.9750
 
 ## 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  | 0.0991          | 0.7455    | 0.7544 | 0.7499 | 0.9701   |
-| No log        | 2.0   | 462  | 0.0849          | 0.7712    | 0.7700 | 0.7706 | 0.9738   |
+| No log        | 1.0   | 231  | 0.0943          | 0.7464    | 0.7612 | 0.7537 | 0.9720   |
+| No log        | 2.0   | 462  | 0.0801          | 0.7861    | 0.7821 | 0.7841 | 0.9750   |
+| 0.2571        | 3.0   | 693  | 0.0806          | 0.7900    | 0.7911 | 0.7906 | 0.9748   |
+| 0.2571        | 4.0   | 924  | 0.0834          | 0.7938    | 0.7935 | 0.7936 | 0.9750   |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.0+cu121
+- Pytorch 2.4.1+cu121
 - Datasets 2.21.0
 - Tokenizers 0.19.1