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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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_2 |
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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: 0.7214503712476654 |
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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_2 |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) 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: 0.8224 |
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- Wer: 0.7215 |
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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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| 5.1374 | 1.0 | 121 | 2.9882 | 1.0 | |
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| 2.9639 | 2.0 | 242 | 2.9334 | 1.0 | |
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| 2.9322 | 3.0 | 363 | 2.9144 | 1.0 | |
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| 2.9198 | 4.0 | 484 | 2.9017 | 1.0 | |
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| 2.8947 | 5.0 | 605 | 2.8740 | 1.0 | |
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| 2.8716 | 6.0 | 726 | 2.8349 | 0.9999 | |
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| 2.8277 | 7.0 | 847 | 2.5051 | 1.0 | |
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| 2.5331 | 8.0 | 968 | 1.4294 | 0.9178 | |
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| 1.6883 | 9.0 | 1089 | 0.9830 | 0.7981 | |
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| 0.9526 | 10.0 | 1210 | 0.8735 | 0.7564 | |
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| 0.8469 | 11.0 | 1331 | 0.8294 | 0.7308 | |
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| 0.83 | 12.0 | 1452 | 0.8224 | 0.7215 | |
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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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