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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- voxpopuli |
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model-index: |
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- name: speecht5_finetuned_voxpopuli_nl |
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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_voxpopuli_nl |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4816 |
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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: 8 |
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- total_train_batch_size: 32 |
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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: 250 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8188 | 0.85 | 50 | 0.7075 | |
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| 0.7124 | 1.71 | 100 | 0.6201 | |
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| 0.6763 | 2.56 | 150 | 0.5924 | |
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| 0.6367 | 3.42 | 200 | 0.5586 | |
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| 0.576 | 4.27 | 250 | 0.5216 | |
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| 0.5591 | 5.13 | 300 | 0.5097 | |
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| 0.5457 | 5.98 | 350 | 0.5027 | |
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| 0.5447 | 6.84 | 400 | 0.4999 | |
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| 0.5413 | 7.69 | 450 | 0.4933 | |
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| 0.5288 | 8.55 | 500 | 0.4913 | |
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| 0.5231 | 9.4 | 550 | 0.4881 | |
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| 0.5276 | 10.26 | 600 | 0.4874 | |
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| 0.52 | 11.11 | 650 | 0.4848 | |
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| 0.5238 | 11.97 | 700 | 0.4863 | |
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| 0.5163 | 12.82 | 750 | 0.4848 | |
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| 0.5191 | 13.68 | 800 | 0.4838 | |
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| 0.5163 | 14.53 | 850 | 0.4828 | |
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| 0.5126 | 15.38 | 900 | 0.4824 | |
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| 0.5155 | 16.24 | 950 | 0.4836 | |
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| 0.5193 | 17.09 | 1000 | 0.4816 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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