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--- |
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language: |
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- gn |
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license: apache-2.0 |
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base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Common Voice 16 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 16 |
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type: mozilla-foundation/common_voice_16_1 |
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config: gn |
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split: None |
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args: gn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 49.766822118587605 |
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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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# Common Voice 16 |
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This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3513 |
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- Wer: 49.7668 |
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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: 1e-05 |
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- train_batch_size: 8 |
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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: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 500 |
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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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| 0.4171 | 1.0152 | 100 | 0.3798 | 55.2965 | |
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| 0.3376 | 2.0305 | 200 | 0.3628 | 53.8974 | |
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| 0.294 | 3.0457 | 300 | 0.3528 | 52.4983 | |
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| 0.2632 | 4.0609 | 400 | 0.3484 | 49.7668 | |
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| 0.2459 | 5.0761 | 500 | 0.3513 | 49.7668 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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