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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_speaking_style_en |
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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_speaking_style_en |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3277 |
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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: 8 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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: 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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| 0.8232 | 0.61 | 100 | 0.5842 | |
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| 0.6949 | 1.23 | 200 | 0.4895 | |
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| 0.4918 | 1.84 | 300 | 0.3843 | |
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| 0.4266 | 2.45 | 400 | 0.3689 | |
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| 0.4098 | 3.07 | 500 | 0.3599 | |
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| 0.4026 | 3.68 | 600 | 0.3593 | |
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| 0.3947 | 4.29 | 700 | 0.3513 | |
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| 0.386 | 4.9 | 800 | 0.3481 | |
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| 0.3809 | 5.52 | 900 | 0.3457 | |
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| 0.3777 | 6.13 | 1000 | 0.3450 | |
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| 0.3745 | 6.74 | 1100 | 0.3418 | |
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| 0.3724 | 7.36 | 1200 | 0.3409 | |
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| 0.3697 | 7.97 | 1300 | 0.3404 | |
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| 0.3687 | 8.58 | 1400 | 0.3379 | |
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| 0.3684 | 9.2 | 1500 | 0.3373 | |
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| 0.3666 | 9.81 | 1600 | 0.3352 | |
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| 0.3637 | 10.42 | 1700 | 0.3395 | |
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| 0.3638 | 11.03 | 1800 | 0.3333 | |
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| 0.3594 | 11.65 | 1900 | 0.3333 | |
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| 0.3603 | 12.26 | 2000 | 0.3378 | |
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| 0.3592 | 12.87 | 2100 | 0.3316 | |
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| 0.3587 | 13.49 | 2200 | 0.3321 | |
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| 0.3557 | 14.1 | 2300 | 0.3311 | |
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| 0.3568 | 14.71 | 2400 | 0.3300 | |
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| 0.3595 | 15.33 | 2500 | 0.3291 | |
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| 0.3565 | 15.94 | 2600 | 0.3323 | |
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| 0.3549 | 16.55 | 2700 | 0.3305 | |
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| 0.3534 | 17.16 | 2800 | 0.3299 | |
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| 0.3545 | 17.78 | 2900 | 0.3268 | |
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| 0.3533 | 18.39 | 3000 | 0.3298 | |
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| 0.3529 | 19.0 | 3100 | 0.3306 | |
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| 0.3526 | 19.62 | 3200 | 0.3285 | |
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| 0.3513 | 20.23 | 3300 | 0.3274 | |
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| 0.3513 | 20.84 | 3400 | 0.3278 | |
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| 0.3505 | 21.46 | 3500 | 0.3295 | |
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| 0.3502 | 22.07 | 3600 | 0.3283 | |
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| 0.3505 | 22.68 | 3700 | 0.3295 | |
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| 0.3527 | 23.3 | 3800 | 0.3289 | |
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| 0.3518 | 23.91 | 3900 | 0.3275 | |
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| 0.3496 | 24.52 | 4000 | 0.3277 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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