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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: XLS-R_Synthesis_ALL_v1 |
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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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# XLS-R_Synthesis_ALL_v1 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1635 |
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- Wer: 0.1696 |
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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: 0.0001 |
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- train_batch_size: 18 |
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- eval_batch_size: 9 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 72 |
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- total_eval_batch_size: 18 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100.0 |
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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 | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 4.5765 | 1.0 | 2611 | 1.4891 | 0.9957 | |
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| 0.7865 | 2.0 | 5223 | 0.3830 | 0.4573 | |
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| 0.4459 | 3.0 | 7834 | 0.2696 | 0.3355 | |
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| 0.3452 | 4.0 | 10446 | 0.2259 | 0.2741 | |
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| 0.2932 | 5.0 | 13057 | 0.2103 | 0.2403 | |
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| 0.2617 | 6.0 | 15669 | 0.1945 | 0.2206 | |
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| 0.2421 | 7.0 | 18280 | 0.1853 | 0.2170 | |
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| 0.2285 | 8.0 | 20892 | 0.1780 | 0.2050 | |
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| 0.2184 | 9.0 | 23503 | 0.1864 | 0.1997 | |
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| 0.2115 | 10.0 | 26115 | 0.1737 | 0.1980 | |
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| 0.2048 | 11.0 | 28726 | 0.1703 | 0.1926 | |
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| 0.195 | 12.0 | 31338 | 0.1830 | 0.1892 | |
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| 0.1864 | 13.0 | 33949 | 0.1676 | 0.1844 | |
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| 0.1785 | 14.0 | 36561 | 0.1609 | 0.1770 | |
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| 0.1727 | 15.0 | 39172 | 0.1690 | 0.1751 | |
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| 0.1676 | 16.0 | 41784 | 0.1639 | 0.1750 | |
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| 0.1638 | 17.0 | 44395 | 0.1634 | 0.1751 | |
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| 0.1594 | 18.0 | 47007 | 0.1659 | 0.1769 | |
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| 0.1553 | 19.0 | 49618 | 0.1635 | 0.1696 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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