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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-1b |
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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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model-index: |
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- name: XLS-R-LUGANDA-ASR-CV-14-1B |
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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_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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- name: Wer |
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type: wer |
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value: 0.30603965548369283 |
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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-CV-14-1B |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) 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: 0.3060 |
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- Cer: 0.0713 |
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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 | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:| |
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| 1.5535 | 0.18 | 400 | 0.1685 | inf | 0.6590 | |
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| 0.539 | 0.36 | 800 | 0.1516 | inf | 0.5934 | |
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| 0.49 | 0.54 | 1200 | 0.1365 | inf | 0.5466 | |
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| 0.4569 | 0.72 | 1600 | 0.1364 | inf | 0.5523 | |
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| 0.4845 | 0.45 | 2000 | 0.1525 | inf | 0.5907 | |
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| 0.4592 | 0.54 | 2400 | 0.1485 | inf | 0.5766 | |
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| 0.4447 | 0.63 | 2800 | 0.1397 | inf | 0.5482 | |
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| 0.426 | 0.72 | 3200 | 0.1352 | inf | 0.5290 | |
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| 0.4454 | 0.81 | 3600 | inf | 0.5330 | 0.1333 | |
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| 0.4188 | 0.9 | 4000 | inf | 0.4903 | 0.1240 | |
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| 0.4083 | 0.99 | 4400 | inf | 0.4857 | 0.1226 | |
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| 0.367 | 1.08 | 4800 | inf | 0.4499 | 0.1114 | |
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| 0.3468 | 1.17 | 5200 | inf | 0.4345 | 0.1063 | |
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| 0.3401 | 1.27 | 5600 | inf | 0.4130 | 0.1009 | |
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| 0.3269 | 1.36 | 6000 | inf | 0.4113 | 0.1004 | |
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| 0.3171 | 1.45 | 6400 | inf | 0.3934 | 0.0956 | |
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| 0.2996 | 1.54 | 6800 | inf | 0.3803 | 0.0913 | |
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| 0.288 | 1.63 | 7200 | inf | 0.3681 | 0.0891 | |
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| 0.2812 | 1.72 | 7600 | inf | 0.3573 | 0.0853 | |
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| 0.2699 | 1.81 | 8000 | inf | 0.3504 | 0.0835 | |
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| 0.2584 | 1.9 | 8400 | inf | 0.3343 | 0.0786 | |
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| 0.2424 | 1.99 | 8800 | inf | 0.3232 | 0.0759 | |
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| 0.2201 | 2.08 | 9200 | inf | 0.3176 | 0.0740 | |
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| 0.2031 | 2.17 | 9600 | inf | 0.3085 | 0.0719 | |
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| 0.2007 | 2.26 | 10000 | inf | 0.3060 | 0.0713 | |
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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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