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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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datasets: |
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- common_voice_7_0 |
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metrics: |
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- wer |
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base_model: facebook/wav2vec2-base |
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model-index: |
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- name: luganda_wav2vec2_ctc_tokenizer |
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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_7_0 |
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type: common_voice_7_0 |
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config: lg |
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split: None |
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args: lg |
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metrics: |
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- type: wer |
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value: 0.5608917697898251 |
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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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# luganda_wav2vec2_ctc_tokenizer |
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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_7_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5588 |
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- Wer: 0.5609 |
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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: 32 |
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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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- lr_scheduler_warmup_steps: 1000 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.1365 | 2.4 | 500 | 1.9598 | 1.0 | |
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| 0.5695 | 4.81 | 1000 | 0.5853 | 0.7329 | |
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| 0.176 | 7.21 | 1500 | 0.5381 | 0.6747 | |
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| 0.0845 | 9.62 | 2000 | 0.5128 | 0.6270 | |
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| 0.0424 | 12.02 | 2500 | 0.4651 | 0.6014 | |
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| 0.0127 | 14.42 | 3000 | 0.5395 | 0.6049 | |
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| -0.0063 | 16.83 | 3500 | 0.5169 | 0.5842 | |
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| -0.0212 | 19.23 | 4000 | 0.4990 | 0.5833 | |
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| -0.0336 | 21.63 | 4500 | 0.5318 | 0.5680 | |
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| -0.0424 | 24.04 | 5000 | 0.5465 | 0.5702 | |
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| -0.0495 | 26.44 | 5500 | 0.5541 | 0.5637 | |
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| -0.0565 | 28.85 | 6000 | 0.5588 | 0.5609 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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