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naqi72
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speecht5_finetuned_hindi_syed_naqi

Text-to-Audio
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speecht5
tts
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End of training

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  1. README.md +21 -9
  2. model.safetensors +1 -1
README.md CHANGED
@@ -19,7 +19,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the TTS_English_data dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4280
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  ## Model description
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@@ -38,7 +38,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 12
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  - eval_batch_size: 10
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  - seed: 42
@@ -46,7 +46,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 24
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 1000
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  - training_steps: 3000
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  - mixed_precision_training: Native AMP
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@@ -54,12 +54,24 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:----:|:---------------:|
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- | 0.5357 | 2.8409 | 500 | 0.4885 |
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- | 0.5014 | 5.6818 | 1000 | 0.4571 |
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- | 0.4728 | 8.5227 | 1500 | 0.4522 |
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- | 0.4518 | 11.3636 | 2000 | 0.4397 |
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- | 0.4472 | 14.2045 | 2500 | 0.4311 |
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- | 0.4383 | 17.0455 | 3000 | 0.4280 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the TTS_English_data dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4244
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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  - train_batch_size: 12
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  - eval_batch_size: 10
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  - seed: 42
 
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  - total_train_batch_size: 24
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 1500
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  - training_steps: 3000
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:----:|:---------------:|
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+ | No log | 1.0 | 176 | 0.7486 |
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+ | 0.9327 | 2.0 | 352 | 0.5466 |
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+ | 0.6633 | 3.0 | 528 | 0.5009 |
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+ | 0.6633 | 4.0 | 704 | 0.4828 |
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+ | 0.5635 | 5.0 | 880 | 0.4694 |
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+ | 0.5364 | 6.0 | 1056 | 0.4601 |
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+ | 0.5364 | 7.0 | 1232 | 0.4609 |
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+ | 0.5155 | 8.0 | 1408 | 0.4463 |
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+ | 0.5025 | 9.0 | 1584 | 0.4459 |
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+ | 0.4883 | 10.0 | 1760 | 0.4399 |
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+ | 0.4883 | 11.0 | 1936 | 0.4342 |
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+ | 0.4792 | 12.0 | 2112 | 0.4359 |
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+ | 0.4715 | 13.0 | 2288 | 0.4264 |
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+ | 0.4715 | 14.0 | 2464 | 0.4273 |
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+ | 0.4646 | 15.0 | 2640 | 0.4238 |
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+ | 0.4598 | 16.0 | 2816 | 0.4231 |
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+ | 0.4598 | 17.0 | 2992 | 0.4227 |
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+ | 0.452 | 17.0455 | 3000 | 0.4244 |
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  ### Framework versions
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