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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: rasr_sample |
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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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# rasr_sample |
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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 common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3149 |
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- Wer: 0.2679 |
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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: 7.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 2000 |
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- num_epochs: 50.0 |
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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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| 3.3332 | 1.45 | 500 | 3.3031 | 1.0 | |
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| 2.9272 | 2.91 | 1000 | 2.9353 | 0.9970 | |
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| 2.0736 | 4.36 | 1500 | 1.1565 | 0.8714 | |
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| 1.7339 | 5.81 | 2000 | 0.7156 | 0.6688 | |
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| 1.5989 | 7.27 | 2500 | 0.5791 | 0.5519 | |
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| 1.4916 | 8.72 | 3000 | 0.5038 | 0.5169 | |
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| 1.4562 | 10.17 | 3500 | 0.4861 | 0.4805 | |
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| 1.3893 | 11.63 | 4000 | 0.4584 | 0.4761 | |
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| 1.3797 | 13.08 | 4500 | 0.4298 | 0.4686 | |
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| 1.3508 | 14.53 | 5000 | 0.4138 | 0.3744 | |
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| 1.3165 | 15.99 | 5500 | 0.4015 | 0.3578 | |
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| 1.281 | 17.44 | 6000 | 0.3883 | 0.3472 | |
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| 1.2682 | 18.89 | 6500 | 0.3904 | 0.3434 | |
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| 1.2477 | 20.35 | 7000 | 0.3726 | 0.3321 | |
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| 1.2364 | 21.8 | 7500 | 0.3685 | 0.3281 | |
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| 1.2041 | 23.26 | 8000 | 0.3597 | 0.3194 | |
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| 1.1901 | 24.71 | 8500 | 0.3542 | 0.3203 | |
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| 1.1903 | 26.16 | 9000 | 0.3500 | 0.3138 | |
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| 1.1677 | 27.61 | 9500 | 0.3458 | 0.3067 | |
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| 1.1718 | 29.07 | 10000 | 0.3595 | 0.3112 | |
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| 1.1562 | 30.52 | 10500 | 0.3433 | 0.3022 | |
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| 1.1392 | 31.97 | 11000 | 0.3440 | 0.2936 | |
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| 1.1258 | 33.43 | 11500 | 0.3396 | 0.2950 | |
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| 1.1067 | 34.88 | 12000 | 0.3379 | 0.2939 | |
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| 1.0953 | 36.34 | 12500 | 0.3370 | 0.2868 | |
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| 1.0835 | 37.79 | 13000 | 0.3317 | 0.2860 | |
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| 1.0772 | 39.24 | 13500 | 0.3302 | 0.2854 | |
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| 1.0853 | 40.7 | 14000 | 0.3265 | 0.2783 | |
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| 1.0689 | 42.15 | 14500 | 0.3306 | 0.2770 | |
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| 1.0394 | 43.6 | 15000 | 0.3233 | 0.2757 | |
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| 1.0581 | 45.06 | 15500 | 0.3199 | 0.2713 | |
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| 1.0362 | 46.51 | 16000 | 0.3154 | 0.2683 | |
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| 1.0406 | 47.96 | 16500 | 0.3176 | 0.2688 | |
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| 1.0082 | 49.42 | 17000 | 0.3149 | 0.2679 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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