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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-xls-r-300m |
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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_Prod19 |
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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: 0.34075405604719766 |
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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_Prod19 |
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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: 0.3575 |
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- Wer: 0.3408 |
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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: 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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| 2.9583 | 1.0 | 278 | 2.9214 | 1.0 | |
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| 2.8606 | 2.0 | 556 | 2.7724 | 1.0 | |
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| 1.1528 | 3.0 | 834 | 0.6902 | 0.6319 | |
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| 0.7003 | 4.0 | 1112 | 0.4844 | 0.4883 | |
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| 0.5853 | 5.0 | 1390 | 0.4030 | 0.4158 | |
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| 0.4685 | 6.0 | 1668 | 0.3945 | 0.3838 | |
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| 0.4273 | 7.0 | 1946 | 0.3824 | 0.3687 | |
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| 0.4116 | 8.0 | 2224 | 0.3643 | 0.3474 | |
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| 0.3858 | 9.0 | 2502 | 0.3575 | 0.3408 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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