nacielo
/

hubert2BertMusic100

@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.7855
-- Rouge1: 20.7363
-- Rouge2: 3.2333
-- Rougel: 16.3746
-- Rougelsum: 16.4147
-- Gen Len: 59.07
 ## Model description
@@ -50,18 +50,18 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
-| 3.3305        | 1.0   | 959  | 3.3111          | 22.9356 | 3.2508 | 17.366  | 17.4075   | 57.61   |
-| 2.9292        | 2.0   | 1918 | 3.1469          | 20.9236 | 3.1184 | 16.3203 | 16.3454   | 55.43   |
-| 2.7957        | 3.0   | 2877 | 3.0347          | 21.339  | 3.6129 | 16.8758 | 16.8954   | 60.23   |
-| 2.7126        | 4.0   | 3836 | 2.9680          | 21.4247 | 3.6279 | 16.5494 | 16.5481   | 59.34   |
-| 2.6505        | 5.0   | 4795 | 2.9066          | 21.3352 | 3.0876 | 16.723  | 16.7403   | 58.91   |
-| 2.6375        | 6.0   | 5754 | 2.8660          | 21.6979 | 3.2778 | 17.0033 | 17.0018   | 59.94   |
-| 2.5865        | 7.0   | 6713 | 2.8287          | 20.2156 | 3.2757 | 16.0352 | 16.0346   | 56.15   |
-| 2.5824        | 8.0   | 7672 | 2.8060          | 22.5532 | 3.5368 | 17.4646 | 17.4785   | 60.47   |
-| 2.5851        | 9.0   | 8631 | 2.7895          | 20.7575 | 3.0594 | 16.2891 | 16.3196   | 59.13   |
-| 2.6084        | 10.0  | 9590 | 2.7855          | 20.7363 | 3.2333 | 16.3746 | 16.4147   | 59.07   |
 ### Framework versions

 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 1.4721
+- Rouge1: 26.5915
+- Rouge2: 7.5185
+- Rougel: 18.8807
+- Rougelsum: 18.8279
+- Gen Len: 56.16
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 1.9005        | 1.0   | 1361  | 1.6875          | 27.9936 | 8.03   | 19.6327 | 19.583    | 52.7    |
+| 1.7493        | 2.0   | 2722  | 1.6272          | 26.1413 | 7.7635 | 18.9764 | 18.8667   | 53.6    |
+| 1.7037        | 3.0   | 4083  | 1.5873          | 27.1884 | 7.3279 | 19.607  | 19.6344   | 56.55   |
+| 1.6621        | 4.0   | 5444  | 1.5505          | 31.0103 | 8.788  | 22.4097 | 22.3902   | 60.45   |
+| 1.6824        | 5.0   | 6805  | 1.5272          | 26.0334 | 7.709  | 18.5954 | 18.5607   | 54.87   |
+| 1.6451        | 6.0   | 8166  | 1.5073          | 30.49   | 7.7309 | 21.4853 | 21.537    | 65.1    |
+| 1.6502        | 7.0   | 9527  | 1.4947          | 30.1318 | 8.4307 | 21.6758 | 21.7107   | 61.48   |
+| 1.6588        | 8.0   | 10888 | 1.4809          | 27.3167 | 7.7378 | 19.4021 | 19.3359   | 57.38   |
+| 1.6896        | 9.0   | 12249 | 1.4737          | 26.7199 | 7.5034 | 18.9846 | 18.9279   | 55.96   |
+| 1.7313        | 10.0  | 13610 | 1.4721          | 26.5915 | 7.5185 | 18.8807 | 18.8279   | 56.16   |
 ### Framework versions