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--- |
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base_model: oyemade/w2v-bert-2.0-yoruba-CV17.0 |
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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-CV17.0 |
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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: 0.10649647551914651 |
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language: |
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- yo |
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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-CV17.0 |
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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: 0.1095 |
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- Wer: 0.1065 |
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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_steps: 500 |
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- num_epochs: 6 |
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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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| 0.3812 | 0.5102 | 100 | 0.3328 | 0.3070 | |
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| 0.2283 | 1.0204 | 200 | 0.2721 | 0.2807 | |
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| 0.1993 | 1.5306 | 300 | 0.3371 | 0.3481 | |
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| 0.2045 | 2.0408 | 400 | 0.3514 | 0.3314 | |
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| 0.2057 | 2.5510 | 500 | 0.3036 | 0.3086 | |
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| 0.2193 | 3.0612 | 600 | 0.2904 | 0.2847 | |
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| 0.1956 | 3.5714 | 700 | 0.2631 | 0.2534 | |
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| 0.1717 | 4.0816 | 800 | 0.1923 | 0.1995 | |
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| 0.1234 | 4.5918 | 900 | 0.1678 | 0.1732 | |
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| 0.0995 | 5.1020 | 1000 | 0.1280 | 0.1341 | |
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| 0.0614 | 5.6122 | 1100 | 0.1095 | 0.1065 | |
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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 2.19.2 |
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- Tokenizers 0.19.1 |
