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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53-spanish |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-gn |
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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_13_0 |
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type: common_voice_13_0 |
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config: gn |
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split: test |
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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: 0.3430613460393091 |
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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-300m-gn |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53-spanish](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-spanish) on the common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3713 |
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- Wer: 0.3431 |
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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: 8 |
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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: 16 |
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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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| 0.7177 | 3.62 | 400 | 0.3649 | 0.5816 | |
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| 0.2738 | 7.24 | 800 | 0.4029 | 0.5024 | |
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| 0.1768 | 10.86 | 1200 | 0.3779 | 0.4285 | |
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| 0.1128 | 14.48 | 1600 | 0.3929 | 0.4205 | |
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| 0.0842 | 18.1 | 2000 | 0.3683 | 0.3916 | |
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| 0.0616 | 21.72 | 2400 | 0.3943 | 0.3675 | |
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| 0.0461 | 25.34 | 2800 | 0.4127 | 0.3571 | |
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| 0.0368 | 28.96 | 3200 | 0.3713 | 0.3431 | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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