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update model card README.md

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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_8_0
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+ model-index:
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+ - name: xlsr_ur_training
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+ results: []
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+ ---
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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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+
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+ # xlsr_ur_training
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_8_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2610
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+ - Wer: 0.7325
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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: 100
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 14.5044 | 1.69 | 100 | 3.9173 | 1.0 |
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+ | 3.3645 | 3.39 | 200 | 3.2475 | 1.0 |
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+ | 3.2318 | 5.08 | 300 | 3.2143 | 1.0 |
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+ | 3.1887 | 6.78 | 400 | 3.1672 | 1.0 |
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+ | 3.1233 | 8.47 | 500 | 3.0927 | 1.0 |
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+ | 3.0938 | 10.17 | 600 | 3.0836 | 0.9970 |
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+ | 3.0706 | 11.86 | 700 | 3.0319 | 0.9996 |
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+ | 2.9622 | 13.56 | 800 | 2.7973 | 0.9985 |
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+ | 2.6267 | 15.25 | 900 | 2.2553 | 0.9974 |
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+ | 1.9748 | 16.95 | 1000 | 1.6858 | 0.9170 |
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+ | 1.4739 | 18.64 | 1100 | 1.4620 | 0.8125 |
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+ | 1.2102 | 20.34 | 1200 | 1.3890 | 0.7779 |
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+ | 1.036 | 22.03 | 1300 | 1.3347 | 0.7672 |
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+ | 0.9462 | 23.73 | 1400 | 1.2970 | 0.7476 |
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+ | 0.8725 | 25.42 | 1500 | 1.2792 | 0.7461 |
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+ | 0.8374 | 27.12 | 1600 | 1.2574 | 0.7384 |
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+ | 0.7976 | 28.81 | 1700 | 1.2610 | 0.7325 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1