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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: wav2vec2-large-xls-r-1b-Indonesian
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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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            # wav2vec2-large-xls-r-1b-Indonesian
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            This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice dataset.
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            It achieves the following results on the evaluation set:
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            - Loss: 0.9550
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            - Wer: 0.4551
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            - Cer: 0.1643
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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: 64
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            - eval_batch_size: 8
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            - seed: 42
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            - gradient_accumulation_steps: 2
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            - total_train_batch_size: 128
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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: 400
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            - num_epochs: 50
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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    | Cer    |
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            |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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            | 3.663         | 7.69  | 200  | 0.7898          | 0.6039 | 0.1848 |
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            | 0.7424        | 15.38 | 400  | 1.0215          | 0.5615 | 0.1924 |
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            | 0.4494        | 23.08 | 600  | 1.0901          | 0.5249 | 0.1932 |
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            | 0.5075        | 30.77 | 800  | 1.1013          | 0.5079 | 0.1935 |
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            | 0.4671        | 38.46 | 1000 | 1.1034          | 0.4916 | 0.1827 |
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            | 0.1928        | 46.15 | 1200 | 0.9550          | 0.4551 | 0.1643 |
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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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