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--- |
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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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model-index: |
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- name: speecht5_finetuned_kazakh_tts2_1 |
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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_kazakh_tts2_1 |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the KazakhTTS2 dataset (Mussakhojayeva, S., Khassanov, Y., & Varol, H.A. (2022). KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics. International Conference on Language Resources and Evaluation). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4600 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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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: 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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| 0.725 | 0.06 | 100 | 0.6639 | |
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| 0.6132 | 0.11 | 200 | 0.5466 | |
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| 0.571 | 0.17 | 300 | 0.5207 | |
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| 0.5647 | 0.22 | 400 | 0.5120 | |
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| 0.5556 | 0.28 | 500 | 0.5047 | |
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| 0.5475 | 0.34 | 600 | 0.5003 | |
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| 0.5432 | 0.39 | 700 | 0.4975 | |
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| 0.5366 | 0.45 | 800 | 0.4944 | |
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| 0.5376 | 0.5 | 900 | 0.4913 | |
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| 0.5325 | 0.56 | 1000 | 0.4868 | |
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| 0.5281 | 0.62 | 1100 | 0.4861 | |
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| 0.5288 | 0.67 | 1200 | 0.4848 | |
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| 0.5251 | 0.73 | 1300 | 0.4825 | |
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| 0.5213 | 0.78 | 1400 | 0.4818 | |
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| 0.5225 | 0.84 | 1500 | 0.4823 | |
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| 0.5199 | 0.9 | 1600 | 0.4812 | |
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| 0.5211 | 0.95 | 1700 | 0.4816 | |
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| 0.5194 | 1.01 | 1800 | 0.4826 | |
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| 0.5224 | 1.06 | 1900 | 0.4798 | |
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| 0.5213 | 1.12 | 2000 | 0.4800 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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