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--- |
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base_model: facebook/wav2vec2-base |
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datasets: |
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- common_voice_13_0 |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: wav2vec2-large-xls-r-vi-colab |
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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: vi |
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split: test[:50%] |
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args: vi |
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metrics: |
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- type: wer |
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value: 0.9155054191550542 |
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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-large-xls-r-vi-colab |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) 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: 2.0995 |
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- Wer: 0.9155 |
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- Cer: 0.4345 |
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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: 16 |
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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: 32 |
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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: 400 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 14.8797 | 4.4444 | 200 | 4.6129 | 1.0 | 1.0 | |
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| 3.9436 | 8.8889 | 400 | 3.5521 | 1.0 | 1.0 | |
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| 3.4845 | 13.3333 | 600 | 3.4997 | 1.0 | 1.0 | |
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| 3.1358 | 17.7778 | 800 | 2.7899 | 1.0011 | 0.7023 | |
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| 2.0727 | 22.2222 | 1000 | 2.2606 | 0.9600 | 0.4680 | |
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| 1.5218 | 26.6667 | 1200 | 2.0995 | 0.9155 | 0.4345 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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