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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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_train_clean |
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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: 0.4156354350815164 |
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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_train_clean |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) 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: 0.2835 |
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- Wer: 0.4156 |
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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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| 5.8861 | 2.4 | 500 | 3.1284 | 1.0 | |
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| 2.0448 | 4.81 | 1000 | 0.5439 | 0.7131 | |
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| 0.6342 | 7.21 | 1500 | 0.3713 | 0.5556 | |
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| 0.4907 | 9.62 | 2000 | 0.3464 | 0.5015 | |
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| 0.4242 | 12.02 | 2500 | 0.3122 | 0.4746 | |
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| 0.3898 | 14.42 | 3000 | 0.3164 | 0.4634 | |
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| 0.357 | 16.83 | 3500 | 0.2896 | 0.4416 | |
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| 0.3338 | 19.23 | 4000 | 0.2880 | 0.4409 | |
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| 0.3223 | 21.63 | 4500 | 0.2841 | 0.4287 | |
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| 0.3072 | 24.04 | 5000 | 0.2849 | 0.4250 | |
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| 0.2974 | 26.44 | 5500 | 0.2829 | 0.4194 | |
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| 0.2878 | 28.85 | 6000 | 0.2835 | 0.4156 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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