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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: tokens |
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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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# tokens |
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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: 0.9811 |
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- Wer: 0.4608 |
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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: 0.0003 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 500 |
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- num_epochs: 30 |
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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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| 6.5212 | 0.59 | 400 | 3.3776 | 1.0 | |
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| 2.4798 | 1.18 | 800 | 1.0697 | 0.7740 | |
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| 1.0057 | 1.77 | 1200 | 0.7077 | 0.6487 | |
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| 0.7731 | 2.36 | 1600 | 0.6113 | 0.5883 | |
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| 0.6917 | 2.94 | 2000 | 0.5618 | 0.5573 | |
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| 0.5844 | 3.53 | 2400 | 0.5610 | 0.5532 | |
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| 0.5606 | 4.12 | 2800 | 0.5584 | 0.5484 | |
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| 0.4973 | 4.71 | 3200 | 0.5466 | 0.5333 | |
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| 0.4721 | 5.3 | 3600 | 0.5495 | 0.5178 | |
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| 0.4439 | 5.89 | 4000 | 0.5667 | 0.5237 | |
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| 0.3965 | 6.48 | 4400 | 0.5865 | 0.5322 | |
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| 0.3876 | 7.07 | 4800 | 0.6099 | 0.5135 | |
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| 0.3407 | 7.66 | 5200 | 0.5891 | 0.5228 | |
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| 0.33 | 8.25 | 5600 | 0.6135 | 0.5072 | |
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| 0.3032 | 8.84 | 6000 | 0.6004 | 0.5028 | |
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| 0.2706 | 9.43 | 6400 | 0.6321 | 0.4991 | |
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| 0.2709 | 10.01 | 6800 | 0.6541 | 0.5051 | |
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| 0.2373 | 10.6 | 7200 | 0.6613 | 0.5119 | |
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| 0.2284 | 11.19 | 7600 | 0.6798 | 0.5086 | |
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| 0.212 | 11.78 | 8000 | 0.6509 | 0.4910 | |
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| 0.1983 | 12.37 | 8400 | 0.7018 | 0.5043 | |
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| 0.1947 | 12.96 | 8800 | 0.6826 | 0.4965 | |
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| 0.1717 | 13.55 | 9200 | 0.7056 | 0.4828 | |
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| 0.1741 | 14.14 | 9600 | 0.7544 | 0.5060 | |
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| 0.1626 | 14.73 | 10000 | 0.7331 | 0.4915 | |
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| 0.1529 | 15.32 | 10400 | 0.7518 | 0.4772 | |
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| 0.1504 | 15.91 | 10800 | 0.7362 | 0.4732 | |
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| 0.1401 | 16.49 | 11200 | 0.7179 | 0.4769 | |
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| 0.1335 | 17.08 | 11600 | 0.7716 | 0.4826 | |
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| 0.1185 | 17.67 | 12000 | 0.7465 | 0.4798 | |
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| 0.1182 | 18.26 | 12400 | 0.8105 | 0.4733 | |
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| 0.1135 | 18.85 | 12800 | 0.7693 | 0.4743 | |
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| 0.1098 | 19.44 | 13200 | 0.8362 | 0.4888 | |
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| 0.1023 | 20.03 | 13600 | 0.8427 | 0.4768 | |
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| 0.1003 | 20.62 | 14000 | 0.8079 | 0.4741 | |
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| 0.0936 | 21.21 | 14400 | 0.8551 | 0.4651 | |
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| 0.0875 | 21.8 | 14800 | 0.8462 | 0.4712 | |
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| 0.0843 | 22.39 | 15200 | 0.9177 | 0.4782 | |
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| 0.0846 | 22.97 | 15600 | 0.8618 | 0.4735 | |
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| 0.08 | 23.56 | 16000 | 0.9017 | 0.4687 | |
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| 0.0789 | 24.15 | 16400 | 0.9034 | 0.4659 | |
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| 0.0717 | 24.74 | 16800 | 0.9690 | 0.4734 | |
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| 0.0714 | 25.33 | 17200 | 0.9395 | 0.4677 | |
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| 0.0699 | 25.92 | 17600 | 0.9222 | 0.4608 | |
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| 0.0658 | 26.51 | 18000 | 0.9222 | 0.4621 | |
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| 0.0612 | 27.1 | 18400 | 0.9691 | 0.4586 | |
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| 0.0583 | 27.69 | 18800 | 0.9647 | 0.4581 | |
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| 0.0596 | 28.28 | 19200 | 0.9820 | 0.4614 | |
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| 0.056 | 28.87 | 19600 | 0.9795 | 0.4596 | |
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| 0.055 | 29.45 | 20000 | 0.9811 | 0.4608 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.3 |
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- Tokenizers 0.10.3 |
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