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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 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-may23-luganda-colab |
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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 |
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type: common_voice |
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config: lg |
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split: test |
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args: lg |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.502121009153829 |
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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-may23-luganda-colab |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7210 |
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- Wer: 0.5021 |
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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: 0.0003 |
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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: 100 |
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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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| 0.0539 | 7.77 | 400 | 0.6641 | 0.5738 | |
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| 0.0725 | 15.53 | 800 | 0.6735 | 0.5932 | |
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| 0.058 | 23.3 | 1200 | 0.6754 | 0.5751 | |
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| 0.0517 | 31.07 | 1600 | 0.6591 | 0.5901 | |
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| 0.0437 | 38.83 | 2000 | 0.7140 | 0.5658 | |
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| 0.0366 | 46.6 | 2400 | 0.7154 | 0.5602 | |
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| 0.0295 | 54.37 | 2800 | 0.6942 | 0.5140 | |
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| 0.0251 | 62.14 | 3200 | 0.7095 | 0.5204 | |
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| 0.0191 | 69.9 | 3600 | 0.7459 | 0.5267 | |
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| 0.0157 | 77.67 | 4000 | 0.6825 | 0.5155 | |
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| 0.0126 | 85.44 | 4400 | 0.7197 | 0.5135 | |
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| 0.0098 | 93.2 | 4800 | 0.7210 | 0.5021 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.3 |
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