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README.md
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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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datasets:
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- google/fleurs
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model-index:
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- name: speecht5_finetuned_fleurs_en_us
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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_fleurs_en_us
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the google/fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4831
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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: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 5
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- training_steps: 54
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.719 | 0.33 | 9 | 0.5634 |
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| 0.5994 | 0.67 | 18 | 0.5290 |
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| 0.584 | 1.0 | 27 | 0.4924 |
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| 0.5589 | 1.33 | 36 | 0.4828 |
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| 0.5747 | 1.67 | 45 | 0.4848 |
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| 0.5904 | 2.0 | 54 | 0.4831 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.3
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- Tokenizers 0.13.3
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