nacielo
/

wav2GPT2MusiSD3200

@@ -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: 1.4619
-- Rouge1: 19.2446
-- Rouge2: 2.6708
-- Rougel: 17.8027
-- Rougelsum: 17.766
-- Gen Len: 76.0
 ## 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 |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
-| 2.7069        | 1.0   | 959  | 2.5357          | 18.3668 | 2.1635 | 17.0926 | 17.0433   | 82.0    |
-| 2.2934        | 2.0   | 1918 | 2.3074          | 17.0518 | 2.1435 | 16.0006 | 15.9772   | 70.0    |
-| 2.1363        | 3.0   | 2877 | 2.1253          | 17.2075 | 2.008  | 16.8224 | 16.7772   | 46.0    |
-| 1.9919        | 4.0   | 3836 | 1.9537          | 17.9258 | 2.0952 | 16.7574 | 16.6999   | 88.0    |
-| 1.8915        | 5.0   | 4795 | 1.8144          | 17.2075 | 2.008  | 16.8224 | 16.7772   | 46.0    |
-| 1.8069        | 6.0   | 5754 | 1.6979          | 15.9274 | 2.3889 | 15.2764 | 15.2325   | 64.0    |
-| 1.7355        | 7.0   | 6713 | 1.5992          | 19.2446 | 2.6708 | 17.8027 | 17.766    | 76.0    |
-| 1.6694        | 8.0   | 7672 | 1.5291          | 19.2446 | 2.6708 | 17.8027 | 17.766    | 76.0    |
-| 1.6216        | 9.0   | 8631 | 1.4830          | 19.2446 | 2.6708 | 17.8027 | 17.766    | 76.0    |
-| 1.5901        | 10.0  | 9590 | 1.4619          | 19.2446 | 2.6708 | 17.8027 | 17.766    | 76.0    |
 ### 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: 1.0719
+- Rouge1: 26.4817
+- Rouge2: 7.5371
+- Rougel: 20.5034
+- Rougelsum: 20.4753
+- Gen Len: 50.0
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 2.3142        | 1.0   | 1361  | 1.9011          | 30.4426 | 7.6822 | 22.0685 | 22.0967   | 65.0    |
+| 1.9704        | 2.0   | 2722  | 1.6765          | 24.8748 | 5.8724 | 20.797  | 20.7737   | 72.0    |
+| 1.8047        | 3.0   | 4083  | 1.5301          | 29.2797 | 7.7402 | 21.8235 | 21.769    | 58.0    |
+| 1.666         | 4.0   | 5444  | 1.4232          | 33.1568 | 8.7277 | 23.07   | 23.013    | 81.0    |
+| 1.5785        | 5.0   | 6805  | 1.3077          | 28.4221 | 7.6332 | 20.5747 | 20.5799   | 55.0    |
+| 1.502         | 6.0   | 8166  | 1.2324          | 27.9706 | 7.7542 | 20.6862 | 20.6696   | 50.0    |
+| 1.4354        | 7.0   | 9527  | 1.1675          | 28.7212 | 7.4616 | 21.8892 | 21.8832   | 46.0    |
+| 1.3681        | 8.0   | 10888 | 1.1178          | 26.8721 | 7.716  | 20.9267 | 20.9161   | 46.0    |
+| 1.3321        | 9.0   | 12249 | 1.0847          | 26.4817 | 7.5371 | 20.5034 | 20.4753   | 50.0    |
+| 1.2997        | 10.0  | 13610 | 1.0719          | 26.4817 | 7.5371 | 20.5034 | 20.4753   | 50.0    |
 ### Framework versions