End of training
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README.md
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---
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library_name: transformers
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license: mit
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base_model: microsoft/speecht5_tts
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_11_0
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model-index:
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- name: speecht5_finetuned_nepali
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# speecht5_finetuned_nepali
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_11_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8532
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 200
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- training_steps: 2000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 0.1549 | 500.0 | 500 | 0.8332 |
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| 0.0983 | 1000.0 | 1000 | 0.8755 |
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| 0.0893 | 1500.0 | 1500 | 0.8254 |
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| 0.1049 | 2000.0 | 2000 | 0.8532 |
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### Framework versions
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- Transformers 4.53.1
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- Pytorch 2.7.1+cu126
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- Datasets 3.6.0
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- Tokenizers 0.21.2
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