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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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-SWAHILI-ASR-CV14 |
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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: sw |
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split: test |
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args: sw |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.21479210182431807 |
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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-SWAHILI-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: 0.2148 |
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- Cer: 0.0684 |
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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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| 3.9008 | 0.33 | 400 | 0.2565 | inf | 0.8327 | |
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| 0.5689 | 0.66 | 800 | 0.1306 | inf | 0.4598 | |
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| 0.3838 | 1.0 | 1200 | 0.1130 | inf | 0.3786 | |
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| 0.3054 | 1.33 | 1600 | 0.1032 | inf | 0.3407 | |
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| 0.2877 | 1.66 | 2000 | 0.0976 | inf | 0.3239 | |
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| 0.2698 | 1.99 | 2400 | 0.0952 | inf | 0.3078 | |
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| 0.2285 | 2.32 | 2800 | 0.0956 | inf | 0.3031 | |
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| 0.224 | 2.66 | 3200 | 0.0892 | inf | 0.2861 | |
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| 0.2224 | 2.99 | 3600 | 0.0877 | inf | 0.2809 | |
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| 0.1906 | 3.32 | 4000 | 0.0853 | inf | 0.2748 | |
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| 0.1897 | 3.65 | 4400 | 0.0844 | inf | 0.2707 | |
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| 0.183 | 3.98 | 4800 | 0.0814 | inf | 0.2614 | |
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| 0.1586 | 4.32 | 5200 | 0.0809 | inf | 0.2569 | |
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| 0.162 | 4.65 | 5600 | 0.0782 | inf | 0.2493 | |
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| 0.1548 | 4.98 | 6000 | 0.0772 | inf | 0.2467 | |
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| 0.1364 | 5.31 | 6400 | 0.0782 | inf | 0.2459 | |
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| 0.1344 | 5.64 | 6800 | 0.0760 | inf | 0.2404 | |
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| 0.1301 | 5.98 | 7200 | 0.0738 | inf | 0.2346 | |
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| 0.1165 | 6.31 | 7600 | inf | 0.2321 | 0.0729 | |
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| 0.1142 | 6.64 | 8000 | inf | 0.2266 | 0.0719 | |
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| 0.1103 | 6.97 | 8400 | inf | 0.2229 | 0.0705 | |
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| 0.101 | 7.3 | 8800 | inf | 0.2203 | 0.0699 | |
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| 0.1006 | 7.63 | 9200 | inf | 0.2174 | 0.0692 | |
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| 0.0958 | 7.97 | 9600 | inf | 0.2160 | 0.0688 | |
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| 0.0896 | 8.3 | 10000 | inf | 0.2148 | 0.0684 | |
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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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