End of training

README.md

@@ -17,15 +17,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [FPTAI/vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0595
-- F1 Micro: 0.7034
-- F1 Macro: 0.0430
-- Accuracy: 0.6374
-- Recall Micro: 0.6094
-- Precision Micro: 0.8317
-- Recall Macro: 0.0392
-- Precision Macro: 0.0621
-- F1: 0.5913
+- Loss: 0.0617
+- F1 Micro: 0.7029
+- F1 Macro: 0.0254
+- Accuracy: 0.6459
+- Recall Micro: 0.6169
+- Precision Micro: 0.8169
+- Recall Macro: 0.0269
+- Precision Macro: 0.0240
+- F1: 0.5817
 
 ## Model description
 
@@ -44,7 +44,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 1e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -57,10 +57,10 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | Recall Micro | Precision Micro | Recall Macro | Precision Macro | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:------------:|:---------------:|:------------:|:---------------:|:------:|
 | 0.0696        | 1.0   | 1526 | 0.0711          | 0.6892   | 0.0243   | 0.7054   | 0.6737       | 0.7054          | 0.0294       | 0.0207          | 0.5573 |
-| 0.055         | 2.0   | 3052 | 0.0622          | 0.6965   | 0.0252   | 0.6345   | 0.6060       | 0.8187          | 0.0265       | 0.0241          | 0.5775 |
-| 0.0631        | 3.0   | 4578 | 0.0598          | 0.7054   | 0.0255   | 0.6436   | 0.6147       | 0.8274          | 0.0268       | 0.0243          | 0.5847 |
-| 0.0534        | 4.0   | 6104 | 0.0591          | 0.6980   | 0.0260   | 0.6268   | 0.5989       | 0.8362          | 0.0265       | 0.0540          | 0.5809 |
-| 0.0296        | 5.0   | 7630 | 0.0595          | 0.7034   | 0.0430   | 0.6374   | 0.6094       | 0.8317          | 0.0392       | 0.0621          | 0.5913 |
+| 0.0577        | 2.0   | 3052 | 0.0640          | 0.6943   | 0.0251   | 0.6398   | 0.6111       | 0.8038          | 0.0267       | 0.0236          | 0.5742 |
+| 0.0674        | 3.0   | 4578 | 0.0613          | 0.6949   | 0.0252   | 0.6257   | 0.5976       | 0.8300          | 0.0261       | 0.0244          | 0.5778 |
+| 0.0576        | 4.0   | 6104 | 0.0610          | 0.7006   | 0.0254   | 0.6358   | 0.6073       | 0.8278          | 0.0265       | 0.0243          | 0.5814 |
+| 0.0387        | 5.0   | 7630 | 0.0617          | 0.7029   | 0.0254   | 0.6459   | 0.6169       | 0.8169          | 0.0269       | 0.0240          | 0.5817 |
 
 
 ### Framework versions

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