End of training
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README.md
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---
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library_name: transformers
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language:
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- hi
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license: mit
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base_model: microsoft/speecht5_tts
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tags:
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- text-to-speech
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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model-index:
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- name: SpeechT5 TTS hindi
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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 TTS hindi
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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: 0.4485
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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: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Use 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: 500
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- training_steps: 4000
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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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| 2.0737 | 16.2602 | 1000 | 0.4705 |
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| 1.8856 | 32.5203 | 2000 | 0.4563 |
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| 1.9033 | 48.7805 | 3000 | 0.4466 |
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| 1.8761 | 65.0407 | 4000 | 0.4485 |
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### Framework versions
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- Transformers 4.46.0.dev0
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.1
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"decoder_start_token_id": 2,
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"eos_token_id": 2,
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"max_length": 1876,
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"pad_token_id": 1,
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"transformers_version": "4.46.0.dev0"
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}
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model.safetensors
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runs/Oct21_10-59-16_1401adfe0856/events.out.tfevents.1729508361.1401adfe0856.540.0
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