End of training

README.md

@@ -21,7 +21,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the TTS_English_Technical_data dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4479
+- Loss: 0.4473
 
 ## Model description
 
@@ -49,29 +49,23 @@ The following hyperparameters were used during training:
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 100
-- num_epochs: 3.0
+- training_steps: 1000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss |
 |:-------------:|:------:|:----:|:---------------:|
-| 5.7875        | 0.1791 | 50   | 0.6062          |
-| 4.5876        | 0.3583 | 100  | 0.5088          |
-| 4.4072        | 0.5374 | 150  | 0.4908          |
-| 4.3177        | 0.7165 | 200  | 0.4883          |
-| 4.1852        | 0.8957 | 250  | 0.4808          |
-| 4.1009        | 1.0748 | 300  | 0.4691          |
-| 4.0833        | 1.2539 | 350  | 0.4677          |
-| 4.0461        | 1.4330 | 400  | 0.4643          |
-| 4.0024        | 1.6122 | 450  | 0.4587          |
-| 3.9729        | 1.7913 | 500  | 0.4593          |
-| 3.9057        | 1.9704 | 550  | 0.4555          |
-| 3.8765        | 2.1496 | 600  | 0.4567          |
-| 3.9148        | 2.3287 | 650  | 0.4541          |
-| 3.8446        | 2.5078 | 700  | 0.4503          |
-| 3.8321        | 2.6870 | 750  | 0.4511          |
-| 3.8683        | 2.8661 | 800  | 0.4479          |
+| 4.6694        | 0.3583 | 100  | 0.5087          |
+| 4.3795        | 0.7165 | 200  | 0.4933          |
+| 4.1725        | 1.0748 | 300  | 0.4727          |
+| 4.061         | 1.4330 | 400  | 0.4695          |
+| 3.9896        | 1.7913 | 500  | 0.4633          |
+| 3.941         | 2.1496 | 600  | 0.4580          |
+| 3.8944        | 2.5078 | 700  | 0.4538          |
+| 3.8968        | 2.8661 | 800  | 0.4522          |
+| 3.79          | 3.2244 | 900  | 0.4499          |
+| 3.8059        | 3.5826 | 1000 | 0.4473          |
 
 
 ### Framework versions