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: 1.4595
-- Rouge1: 46.5222
-- Rouge2: 18.6099
-- Rougel: 33.3774
-- Rougelsum: 33.3798
-- Gen Len: 39.0
 ## 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 |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
-| 2.4666        | 1.0   | 983  | 1.8573          | 38.068  | 13.843  | 29.5331 | 29.5373   | 33.0    |
-| 2.0055        | 2.0   | 1966 | 1.7201          | 38.0701 | 11.4181 | 30.4599 | 30.4934   | 29.0    |
-| 1.8958        | 3.0   | 2949 | 1.6381          | 45.7986 | 18.9877 | 33.2071 | 33.1974   | 43.0    |
-| 1.8108        | 4.0   | 3932 | 1.5818          | 37.4842 | 13.0246 | 30.5066 | 30.5385   | 34.0    |
-| 1.7778        | 5.0   | 4915 | 1.5410          | 38.3821 | 13.7607 | 30.4166 | 30.4494   | 28.0    |
-| 1.7521        | 6.0   | 5898 | 1.5077          | 46.5222 | 18.6099 | 33.3774 | 33.3798   | 39.0    |
-| 1.7425        | 7.0   | 6881 | 1.4850          | 43.6827 | 18.3618 | 33.0652 | 33.0676   | 43.0    |
-| 1.7455        | 8.0   | 7864 | 1.4682          | 43.6827 | 18.3618 | 33.0652 | 33.0676   | 43.0    |
-| 1.7459        | 9.0   | 8847 | 1.4621          | 46.5222 | 18.6099 | 33.3774 | 33.3798   | 39.0    |
-| 1.7544        | 10.0  | 9830 | 1.4595          | 46.5222 | 18.6099 | 33.3774 | 33.3798   | 39.0    |
 ### 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: 1.4136
+- Rouge1: 18.3305
+- Rouge2: 2.3398
+- Rougel: 16.1355
+- Rougelsum: 16.0889
+- Gen Len: 68.0
 ## Model description
 ### Training results
+| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
+| 1.9475        | 1.0   | 959  | 1.7999          | 21.7144 | 2.959  | 19.633  | 19.6005   | 63.0    |
+| 1.7055        | 2.0   | 1918 | 1.6840          | 21.3721 | 2.9057 | 19.166  | 19.142    | 61.0    |
+| 1.6262        | 3.0   | 2877 | 1.6052          | 19.3952 | 2.692  | 17.8213 | 17.7863   | 76.0    |
+| 1.5601        | 4.0   | 3836 | 1.5495          | 18.0278 | 2.2993 | 16.1559 | 16.1154   | 68.0    |
+| 1.5354        | 5.0   | 4795 | 1.4992          | 18.1503 | 2.1188 | 15.9452 | 15.9245   | 62.0    |
+| 1.5294        | 6.0   | 5754 | 1.4659          | 18.0278 | 2.2993 | 16.1559 | 16.1154   | 68.0    |
+| 1.5278        | 7.0   | 6713 | 1.4371          | 16.5149 | 2.4707 | 15.8236 | 15.7624   | 60.0    |
+| 1.5306        | 8.0   | 7672 | 1.4223          | 18.7176 | 2.4645 | 16.5148 | 16.4705   | 62.0    |
+| 1.5477        | 9.0   | 8631 | 1.4148          | 18.3305 | 2.3398 | 16.1355 | 16.0889   | 68.0    |
+| 1.5722        | 10.0  | 9590 | 1.4136          | 18.3305 | 2.3398 | 16.1355 | 16.0889   | 68.0    |
 ### Framework versions