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: 2.7504
-- Rouge1: 22.5784
-- Rouge2: 3.4041
-- Rougel: 17.4088
-- Rougelsum: 17.4611
-- Gen Len: 61.17
 ## 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 |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
-| 4.6121        | 1.0   | 959  | 4.4012          | 23.8355 | 3.7484 | 17.1657 | 17.2033   | 63.29   |
-| 3.7979        | 2.0   | 1918 | 3.9640          | 22.1613 | 2.7656 | 16.2795 | 16.3033   | 60.23   |
-| 3.4556        | 3.0   | 2877 | 3.6464          | 23.4398 | 3.3542 | 17.9256 | 17.9306   | 64.06   |
-| 3.2176        | 4.0   | 3836 | 3.3747          | 22.1775 | 3.0859 | 17.307  | 17.3082   | 61.06   |
-| 3.0363        | 5.0   | 4795 | 3.1786          | 21.1054 | 2.7657 | 16.8919 | 16.8975   | 54.02   |
-| 2.9271        | 6.0   | 5754 | 3.0308          | 20.891  | 2.7159 | 16.5669 | 16.5785   | 43.6    |
-| 2.7874        | 7.0   | 6713 | 2.9043          | 20.275  | 2.7398 | 16.1674 | 16.203    | 56.45   |
-| 2.7099        | 8.0   | 7672 | 2.8298          | 21.2601 | 2.998  | 16.5244 | 16.5281   | 58.98   |
-| 2.6453        | 9.0   | 8631 | 2.7744          | 22.4683 | 2.8918 | 17.1441 | 17.1683   | 55.41   |
-| 2.6149        | 10.0  | 9590 | 2.7504          | 22.5784 | 3.4041 | 17.4088 | 17.4611   | 61.17   |
 ### 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: 1.5608
+- Rouge1: 26.8788
+- Rouge2: 7.7875
+- Rougel: 19.0867
+- Rougelsum: 19.0059
+- Gen Len: 52.68
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 3.184         | 1.0   | 1361  | 2.6115          | 25.0008 | 7.7596 | 19.0824 | 19.0223   | 46.0    |
+| 2.5657        | 2.0   | 2722  | 2.2430          | 25.4109 | 4.9388 | 18.851  | 18.8614   | 52.19   |
+| 2.3496        | 3.0   | 4083  | 2.0430          | 26.517  | 7.6506 | 18.9172 | 18.8696   | 56.45   |
+| 2.2011        | 4.0   | 5444  | 1.9079          | 27.1096 | 7.7201 | 19.2615 | 19.2315   | 52.62   |
+| 2.1264        | 5.0   | 6805  | 1.8010          | 25.8208 | 6.5427 | 18.2762 | 18.2818   | 56.84   |
+| 1.9913        | 6.0   | 8166  | 1.7185          | 32.4549 | 8.4658 | 22.9767 | 22.9609   | 67.77   |
+| 1.9133        | 7.0   | 9527  | 1.6602          | 26.8271 | 7.4957 | 19.093  | 19.0392   | 50.07   |
+| 1.8605        | 8.0   | 10888 | 1.6075          | 29.8012 | 8.5321 | 21.3029 | 21.2936   | 63.94   |
+| 1.8227        | 9.0   | 12249 | 1.5714          | 27.1868 | 7.8113 | 19.1224 | 19.0768   | 57.59   |
+| 1.7965        | 10.0  | 13610 | 1.5608          | 26.8788 | 7.7875 | 19.0867 | 19.0059   | 52.68   |
 ### Framework versions