Model save

README.md

@@ -21,11 +21,11 @@ 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0466
-- Precision: 0.9352
-- Recall: 0.9444
-- F1: 0.9398
-- Accuracy: 0.9871
+- Loss: 0.1584
+- Precision: 0.8561
+- Recall: 0.8582
+- F1: 0.8571
+- Accuracy: 0.9595
 
 ## Model description
 
@@ -57,14 +57,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2237        | 1.0   | 164  | 0.0972          | 0.8813    | 0.8582 | 0.8696 | 0.9729   |
-| 0.0868        | 2.0   | 328  | 0.0510          | 0.9203    | 0.9324 | 0.9263 | 0.9851   |
-| 0.069         | 3.0   | 492  | 0.0466          | 0.9352    | 0.9444 | 0.9398 | 0.9871   |
+| 0.2274        | 1.0   | 250  | 0.2252          | 0.8585    | 0.8030 | 0.8298 | 0.9435   |
+| 0.1323        | 2.0   | 500  | 0.1693          | 0.8376    | 0.8413 | 0.8394 | 0.9524   |
+| 0.1022        | 3.0   | 750  | 0.1584          | 0.8561    | 0.8582 | 0.8571 | 0.9595   |
 
 
 ### Framework versions
 
 - Transformers 4.57.1
-- Pytorch 2.8.0+cu126
+- Pytorch 2.9.0+cu126
 - Datasets 4.4.1
 - Tokenizers 0.22.1

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