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 [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1130
-- Precision: 0.9419
-- Recall: 0.9533
-- F1: 0.9476
-- Accuracy: 0.9765
+- Loss: 0.1614
+- Precision: 0.9454
+- Recall: 0.9534
+- F1: 0.9494
+- Accuracy: 0.9550
 
 ## Model description
 
@@ -55,9 +55,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1281        | 1.0   | 6242  | 0.1079          | 0.9280    | 0.9363 | 0.9321 | 0.9721   |
-| 0.0883        | 2.0   | 12484 | 0.1069          | 0.9330    | 0.9496 | 0.9412 | 0.9746   |
-| 0.0431        | 3.0   | 18726 | 0.1130          | 0.9419    | 0.9533 | 0.9476 | 0.9765   |
+| 0.1526        | 1.0   | 6242  | 0.1463          | 0.9328    | 0.9483 | 0.9405 | 0.9526   |
+| 0.0957        | 2.0   | 12484 | 0.1250          | 0.9420    | 0.9514 | 0.9467 | 0.9663   |
+| 0.0889        | 3.0   | 18726 | 0.1614          | 0.9454    | 0.9534 | 0.9494 | 0.9550   |
 
 
 ### Framework versions