End of training

README.md

@@ -23,7 +23,7 @@ model-index:
     metrics:
     - name: Bleu
       type: bleu
-      value: 7.115012632579186
+      value: 6.051969601236915
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ 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: 5.2494
-- Model Preparation Time: 0.017
-- Bleu: 7.1150
+- Loss: 5.2440
+- Model Preparation Time: 0.0028
+- Bleu: 6.0520
 
 ## Model description
 
@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Bleu   |
 |:-------------:|:------:|:----:|:---------------:|:----------------------:|:------:|
-| 6.8083        | 0.0476 | 500  | 6.7542          | 0.017                  | 4.6732 |
-| 6.1556        | 0.0952 | 1000 | 6.2083          | 0.017                  | 4.3588 |
-| 5.9295        | 0.1427 | 1500 | 5.9114          | 0.017                  | 4.5718 |
-| 5.7926        | 0.1903 | 2000 | 5.7025          | 0.017                  | 5.9611 |
-| 5.4625        | 0.2379 | 2500 | 5.5511          | 0.017                  | 6.0040 |
-| 5.4432        | 0.2855 | 3000 | 5.4391          | 0.017                  | 6.8646 |
-| 5.2127        | 0.3330 | 3500 | 5.3516          | 0.017                  | 6.6020 |
-| 5.5486        | 0.3806 | 4000 | 5.2969          | 0.017                  | 7.3200 |
-| 5.3347        | 0.4282 | 4500 | 5.2653          | 0.017                  | 7.2014 |
-| 5.4594        | 0.4758 | 5000 | 5.2494          | 0.017                  | 7.1159 |
+| 6.7996        | 0.0476 | 500  | 6.7513          | 0.0028                 | 3.5511 |
+| 6.1464        | 0.0952 | 1000 | 6.2017          | 0.0028                 | 5.0638 |
+| 5.927         | 0.1427 | 1500 | 5.9045          | 0.0028                 | 5.1608 |
+| 5.7975        | 0.1903 | 2000 | 5.6937          | 0.0028                 | 5.1830 |
+| 5.4751        | 0.2379 | 2500 | 5.5416          | 0.0028                 | 4.7912 |
+| 5.4717        | 0.2855 | 3000 | 5.4346          | 0.0028                 | 6.3369 |
+| 5.2174        | 0.3330 | 3500 | 5.3458          | 0.0028                 | 4.9379 |
+| 5.5536        | 0.3806 | 4000 | 5.2918          | 0.0028                 | 5.7794 |
+| 5.3342        | 0.4282 | 4500 | 5.2603          | 0.0028                 | 6.3629 |
+| 5.4492        | 0.4758 | 5000 | 5.2440          | 0.0028                 | 6.0904 |
 
 
 ### Framework versions