End of training

README.md

@@ -14,13 +14,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0503
-- F1 Micro: 0.7151
-- F1 Macro: 0.0389
-- Recall Micro: 0.5966
-- Precision Micro: 0.8923
-- Recall Macro: 0.0345
-- Precision Macro: 0.0667
+- Loss: 0.0541
+- F1 Micro: 0.7087
+- F1 Macro: 0.0259
+- Recall Micro: 0.5880
+- Precision Micro: 0.8918
+- Recall Macro: 0.0257
+- Precision Macro: 0.0262
 
 ## Model description
 
@@ -45,15 +45,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Recall Micro | Precision Micro | Recall Macro | Precision Macro |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------------:|:---------------:|:------------:|:---------------:|
-| 0.0634        | 1.0   | 1526 | 0.0617          | 0.7043   | 0.0257   | 0.5959       | 0.8608          | 0.0260       | 0.0253          |
-| 0.0433        | 2.0   | 3052 | 0.0536          | 0.7085   | 0.0259   | 0.5957       | 0.8740          | 0.0260       | 0.0257          |
-| 0.0496        | 3.0   | 4578 | 0.0503          | 0.7151   | 0.0389   | 0.5966       | 0.8923          | 0.0345       | 0.0667          |
+| 0.069         | 1.0   | 1526 | 0.0706          | 0.6892   | 0.0243   | 0.6737       | 0.7054          | 0.0294       | 0.0207          |
+| 0.0512        | 2.0   | 3052 | 0.0636          | 0.7055   | 0.0255   | 0.6165       | 0.8245          | 0.0269       | 0.0243          |
+| 0.0629        | 3.0   | 4578 | 0.0577          | 0.7013   | 0.0257   | 0.5812       | 0.8840          | 0.0254       | 0.0260          |
+| 0.0574        | 4.0   | 6104 | 0.0550          | 0.7120   | 0.0259   | 0.6024       | 0.8706          | 0.0263       | 0.0256          |
+| 0.0375        | 5.0   | 7630 | 0.0541          | 0.7087   | 0.0259   | 0.5880       | 0.8918          | 0.0257       | 0.0262          |
 
 
 ### Framework versions

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