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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_14_0 |
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metrics: |
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- wer |
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base_model: facebook/wav2vec2-xls-r-300m |
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model-index: |
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- name: XLS-R-LUGANDA-ASR-CV14 |
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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_14_0 |
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type: common_voice_14_0 |
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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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- type: wer |
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value: 0.2406197895094572 |
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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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# XLS-R-LUGANDA-ASR-CV14 |
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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_14_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.2406 |
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- Cer: 0.0537 |
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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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- training_steps: 10000 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 4.24 | 0.18 | 400 | inf | 0.8354 | 0.2170 | |
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| 0.6124 | 0.36 | 800 | inf | 0.5690 | 0.1360 | |
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| 0.4411 | 0.54 | 1200 | inf | 0.4746 | 0.1120 | |
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| 0.3839 | 0.72 | 1600 | inf | 0.4409 | 0.1050 | |
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| 0.3504 | 0.9 | 2000 | inf | 0.3955 | 0.0943 | |
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| 0.3214 | 1.08 | 2400 | inf | 0.3678 | 0.0854 | |
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| 0.2879 | 1.26 | 2800 | inf | 0.3614 | 0.0836 | |
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| 0.284 | 1.45 | 3200 | inf | 0.3411 | 0.0789 | |
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| 0.2683 | 1.63 | 3600 | inf | 0.3362 | 0.0767 | |
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| 0.2572 | 1.81 | 4000 | inf | 0.3241 | 0.0740 | |
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| 0.2532 | 1.99 | 4400 | inf | 0.3117 | 0.0719 | |
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| 0.2228 | 2.17 | 4800 | inf | 0.2977 | 0.0677 | |
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| 0.2143 | 2.35 | 5200 | inf | 0.2969 | 0.0676 | |
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| 0.211 | 2.53 | 5600 | inf | 0.2918 | 0.0665 | |
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| 0.2066 | 2.71 | 6000 | inf | 0.2848 | 0.0647 | |
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| 0.2026 | 2.89 | 6400 | inf | 0.2804 | 0.0637 | |
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| 0.1898 | 3.07 | 6800 | inf | 0.2744 | 0.0627 | |
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| 0.1747 | 3.25 | 7200 | inf | 0.2668 | 0.0603 | |
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| 0.1667 | 3.43 | 7600 | inf | 0.2631 | 0.0597 | |
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| 0.1639 | 3.61 | 8000 | inf | 0.2558 | 0.0580 | |
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| 0.1601 | 3.79 | 8400 | inf | 0.2519 | 0.0567 | |
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| 0.1546 | 3.98 | 8800 | inf | 0.2487 | 0.0554 | |
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| 0.1395 | 4.16 | 9200 | inf | 0.2449 | 0.0551 | |
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| 0.1364 | 4.34 | 9600 | inf | 0.2425 | 0.0542 | |
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| 0.1341 | 4.52 | 10000 | inf | 0.2406 | 0.0537 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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