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--- |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-yoruba-colab-CV17.0-v2 |
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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_17_0 |
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type: common_voice_17_0 |
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config: yo |
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split: test |
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args: yo |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5771575538197752 |
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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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# w2v-bert-2.0-yoruba-colab-CV17.0-v2 |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8450 |
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- Wer: 0.5772 |
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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: 5e-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_ratio: 0.15 |
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- training_steps: 2000 |
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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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| 2.7641 | 3.0769 | 200 | 1.0220 | 0.7877 | |
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| 0.6684 | 6.1538 | 400 | 0.9003 | 0.6490 | |
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| 0.4959 | 9.2308 | 600 | 0.9080 | 0.7072 | |
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| 0.359 | 12.3077 | 800 | 0.9788 | 0.6147 | |
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| 0.2047 | 15.3846 | 1000 | 1.0914 | 0.6017 | |
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| 0.0858 | 18.4615 | 1200 | 1.4604 | 0.5973 | |
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| 0.0426 | 21.5385 | 1400 | 1.5740 | 0.5988 | |
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| 0.0088 | 24.6154 | 1600 | 1.7418 | 0.5753 | |
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| 0.0017 | 27.6923 | 1800 | 1.8206 | 0.5779 | |
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| 0.001 | 30.7692 | 2000 | 1.8450 | 0.5772 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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