End of training

README.md

@@ -18,12 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0962
-- Rouge1: 0.76
-- Rouge2: 0.6246
-- Rougel: 0.7508
-- Sacrebleu: 53.9078
-- Gen Len: 32.9976
+- Loss: 0.0810
+- Rouge1: 0.8026
+- Rouge2: 0.6711
+- Rougel: 0.796
+- Sacrebleu: 55.7975
+- Gen Len: 33.3938
 
 ## Model description
 
@@ -43,11 +43,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 2
-- eval_batch_size: 2
+- train_batch_size: 4
+- eval_batch_size: 4
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 4
+- total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
@@ -57,14 +57,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu | Gen Len |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
-| 0.0639        | 1.0   | 418  | 0.0779          | 0.7012 | 0.5432 | 0.6904 | 43.0798   | 32.9976 |
-| 0.0653        | 2.0   | 836  | 0.0732          | 0.7197 | 0.5593 | 0.7091 | 44.8483   | 32.9976 |
-| 0.0327        | 3.0   | 1254 | 0.0726          | 0.7319 | 0.5787 | 0.7206 | 47.842    | 32.9976 |
-| 0.0168        | 4.0   | 1672 | 0.0782          | 0.7466 | 0.6031 | 0.7371 | 50.9225   | 32.9976 |
-| 0.013         | 5.0   | 2090 | 0.0804          | 0.7507 | 0.6077 | 0.7409 | 51.8293   | 32.9976 |
-| 0.0032        | 6.0   | 2508 | 0.0846          | 0.7606 | 0.6237 | 0.7507 | 53.5224   | 32.9976 |
-| 0.0012        | 7.0   | 2926 | 0.0911          | 0.7597 | 0.6263 | 0.751  | 54.0182   | 32.9976 |
-| 0.0012        | 8.0   | 3344 | 0.0962          | 0.76   | 0.6246 | 0.7508 | 53.9078   | 32.9976 |
+| 0.0978        | 1.0   | 209  | 0.0948          | 0.6734 | 0.5117 | 0.664  | 43.1877   | 33.3938 |
+| 0.0617        | 2.0   | 418  | 0.0598          | 0.7702 | 0.6222 | 0.7609 | 49.5794   | 33.3938 |
+| 1.1021        | 3.0   | 627  | 0.8158          | 0.0161 | 0.0    | 0.0162 | 0.0009    | 34.3938 |
+| 0.0471        | 4.0   | 836  | 0.0822          | 0.6874 | 0.5335 | 0.6779 | 44.9573   | 33.3938 |
+| 0.0276        | 5.0   | 1045 | 0.0664          | 0.7767 | 0.6339 | 0.7686 | 52.2135   | 33.3938 |
+| 0.0162        | 6.0   | 1254 | 0.0756          | 0.7856 | 0.6452 | 0.7796 | 50.4352   | 33.3938 |
+| 0.0069        | 7.0   | 1463 | 0.0796          | 0.7939 | 0.6586 | 0.7877 | 52.9489   | 33.3938 |
+| 0.0051        | 8.0   | 1672 | 0.0810          | 0.8026 | 0.6711 | 0.796  | 55.7975   | 33.3938 |
 
 
 ### Framework versions