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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-SWAHILI-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: 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: 0.2794303764906829 |
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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-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: 0.2794 |
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- Cer: 0.0903 |
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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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| 1.9691 | 0.33 | 400 | 0.2374 | inf | 0.6776 | |
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| 0.5464 | 0.66 | 800 | 0.1758 | inf | 0.5598 | |
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| 0.4909 | 1.0 | 1200 | 0.1680 | inf | 0.5243 | |
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| 0.4263 | 1.33 | 1600 | 0.1502 | inf | 0.4706 | |
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| 0.4047 | 1.66 | 2000 | 0.1580 | inf | 0.4858 | |
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| 0.4054 | 1.99 | 2400 | 0.1426 | inf | 0.4348 | |
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| 0.3542 | 2.32 | 2800 | 0.1340 | inf | 0.4185 | |
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| 0.3525 | 2.66 | 3200 | 0.1400 | inf | 0.4311 | |
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| 0.3359 | 2.99 | 3600 | 0.1308 | inf | 0.4012 | |
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| 0.3006 | 3.32 | 4000 | 0.1278 | inf | 0.3939 | |
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| 0.326 | 1.83 | 4400 | inf | 0.4232 | 0.1362 | |
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| 0.326 | 1.99 | 4800 | inf | 0.4136 | 0.1350 | |
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| 0.3034 | 2.16 | 5200 | inf | 0.4282 | 0.1419 | |
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| 0.2925 | 2.32 | 5600 | inf | 0.3901 | 0.1282 | |
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| 0.2822 | 2.49 | 6000 | inf | 0.3876 | 0.1270 | |
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| 0.2659 | 2.66 | 6400 | inf | 0.3586 | 0.1159 | |
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| 0.2582 | 2.82 | 6800 | inf | 0.3536 | 0.1168 | |
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| 0.2414 | 2.99 | 7200 | inf | 0.3327 | 0.1069 | |
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| 0.208 | 3.15 | 7600 | inf | 0.3249 | 0.1053 | |
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| 0.1934 | 3.32 | 8000 | inf | 0.3120 | 0.1015 | |
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| 0.1881 | 3.49 | 8400 | inf | 0.3058 | 0.0993 | |
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| 0.1774 | 3.65 | 8800 | inf | 0.2962 | 0.0959 | |
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| 0.1736 | 3.82 | 9200 | inf | 0.2902 | 0.0935 | |
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| 0.1679 | 3.98 | 9600 | inf | 0.2843 | 0.0917 | |
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| 0.1436 | 4.15 | 10000 | inf | 0.2794 | 0.0903 | |
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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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