End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Bleu
       type: bleu
-      value: 48.97187699036763
+      value: 48.8947659869222
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset.
 It achieves the following results on the evaluation set:
 - Loss: 1.0255
-- Model Preparation Time: 0.0027
-- Bleu: 48.9719
+- Model Preparation Time: 0.0056
+- Bleu: 48.8948
 
 ## Model description
 
@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Bleu    |
 |:-------------:|:------:|:----:|:---------------:|:----------------------:|:-------:|
-| 1.4006        | 0.0476 | 500  | 1.2424          | 0.0027                 | 45.5632 |
-| 1.1468        | 0.0952 | 1000 | 1.1651          | 0.0027                 | 46.9570 |
-| 1.0415        | 0.1427 | 1500 | 1.1203          | 0.0027                 | 47.7010 |
-| 1.1744        | 0.1903 | 2000 | 1.0877          | 0.0027                 | 44.0314 |
-| 1.1875        | 0.2379 | 2500 | 1.0665          | 0.0027                 | 48.6355 |
-| 1.1702        | 0.2855 | 3000 | 1.0510          | 0.0027                 | 47.1142 |
-| 1.0369        | 0.3330 | 3500 | 1.0385          | 0.0027                 | 48.8440 |
-| 1.1669        | 0.3806 | 4000 | 1.0325          | 0.0027                 | 49.0359 |
-| 1.1349        | 0.4282 | 4500 | 1.0279          | 0.0027                 | 48.7849 |
-| 1.0435        | 0.4758 | 5000 | 1.0255          | 0.0027                 | 49.1007 |
+| 1.4007        | 0.0476 | 500  | 1.2424          | 0.0056                 | 45.5942 |
+| 1.1468        | 0.0952 | 1000 | 1.1651          | 0.0056                 | 46.9449 |
+| 1.0415        | 0.1427 | 1500 | 1.1203          | 0.0056                 | 47.6958 |
+| 1.1744        | 0.1903 | 2000 | 1.0877          | 0.0056                 | 44.0503 |
+| 1.1876        | 0.2379 | 2500 | 1.0665          | 0.0056                 | 48.6443 |
+| 1.1702        | 0.2855 | 3000 | 1.0510          | 0.0056                 | 47.1173 |
+| 1.0369        | 0.3330 | 3500 | 1.0385          | 0.0056                 | 48.8846 |
+| 1.1668        | 0.3806 | 4000 | 1.0325          | 0.0056                 | 49.0365 |
+| 1.1351        | 0.4282 | 4500 | 1.0279          | 0.0056                 | 48.8962 |
+| 1.0436        | 0.4758 | 5000 | 1.0255          | 0.0056                 | 49.0433 |
 
 
 ### Framework versions