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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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: XLS-R-demo-google-colab-Ezra_William_Prod_3 |
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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: id |
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split: validation |
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args: id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.697900059217419 |
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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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# XLS-R-demo-google-colab-Ezra_William_Prod_3 |
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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: 0.7896 |
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- Wer: 0.6979 |
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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: 0.0001 |
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- train_batch_size: 16 |
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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: 12 |
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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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| 5.4479 | 1.0 | 121 | 2.9741 | 1.0 | |
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| 2.9543 | 2.0 | 242 | 2.9297 | 1.0 | |
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| 2.9306 | 3.0 | 363 | 2.9112 | 1.0 | |
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| 2.9216 | 4.0 | 484 | 2.9071 | 1.0 | |
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| 2.8968 | 5.0 | 605 | 2.8713 | 1.0 | |
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| 2.8822 | 6.0 | 726 | 2.8446 | 1.0 | |
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| 2.8421 | 7.0 | 847 | 2.5157 | 1.0 | |
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| 2.5763 | 8.0 | 968 | 1.5780 | 0.9964 | |
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| 1.9449 | 9.0 | 1089 | 0.9864 | 0.8132 | |
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| 1.0398 | 10.0 | 1210 | 0.8565 | 0.7348 | |
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| 0.9162 | 11.0 | 1331 | 0.7941 | 0.7043 | |
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| 0.8909 | 12.0 | 1452 | 0.7896 | 0.6979 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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