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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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base_model: facebook/wav2vec2-large-xlsr-53 |
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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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod13 |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: 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: id |
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split: test |
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args: id |
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metrics: |
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- type: wer |
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value: 0.48557337758112096 |
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name: Wer |
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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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod13 |
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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_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5016 |
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- Wer: 0.4856 |
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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: 3e-05 |
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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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- num_epochs: 9 |
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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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| 4.6797 | 0.9 | 500 | 2.9506 | 1.0 | |
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| 2.9108 | 1.8 | 1000 | 2.8667 | 1.0 | |
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| 2.718 | 2.7 | 1500 | 2.0670 | 1.0 | |
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| 1.6297 | 3.6 | 2000 | 0.8461 | 0.7156 | |
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| 1.0568 | 4.5 | 2500 | 0.6528 | 0.5982 | |
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| 0.8918 | 5.4 | 3000 | 0.5682 | 0.5455 | |
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| 0.8099 | 6.29 | 3500 | 0.5385 | 0.5166 | |
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| 0.7528 | 7.19 | 4000 | 0.5152 | 0.4994 | |
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| 0.71 | 8.09 | 4500 | 0.5002 | 0.4882 | |
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| 0.71 | 8.99 | 5000 | 0.5016 | 0.4856 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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