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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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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model-index: |
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- name: luganda_wav2vec2_ctc |
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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_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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- name: Wer |
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type: wer |
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value: 0.5421986512145617 |
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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 |
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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: 0.7622 |
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- Wer: 0.5422 |
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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: 48 |
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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: 60 |
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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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| 4.2675 | 3.6 | 500 | 1.9999 | 0.9999 | |
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| 0.5754 | 7.19 | 1000 | 0.6976 | 0.7050 | |
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| 0.231 | 10.79 | 1500 | 0.6153 | 0.6440 | |
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| 0.1557 | 14.39 | 2000 | 0.6581 | 0.6130 | |
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| 0.1221 | 17.99 | 2500 | 0.6718 | 0.6063 | |
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| 0.1013 | 21.58 | 3000 | 0.6711 | 0.5934 | |
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| 0.0871 | 25.18 | 3500 | 0.6728 | 0.5731 | |
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| 0.0751 | 28.78 | 4000 | 0.6729 | 0.5726 | |
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| 0.0666 | 32.37 | 4500 | 0.6884 | 0.5689 | |
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| 0.0604 | 35.97 | 5000 | 0.7452 | 0.5609 | |
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| 0.0543 | 39.57 | 5500 | 0.7302 | 0.5616 | |
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| 0.0488 | 43.17 | 6000 | 0.7414 | 0.5480 | |
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| 0.0448 | 46.76 | 6500 | 0.7662 | 0.5560 | |
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| 0.042 | 50.36 | 7000 | 0.7629 | 0.5433 | |
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| 0.038 | 53.96 | 7500 | 0.7582 | 0.5479 | |
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| 0.0353 | 57.55 | 8000 | 0.7622 | 0.5422 | |
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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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