| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-xls-r-300m |
| tags: |
| - generated_from_trainer |
| datasets: |
| - common_voice_14_0 |
| metrics: |
| - wer |
| model-index: |
| - name: XLS-R-SWAHILI-ASR-CV14 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice_14_0 |
| type: common_voice_14_0 |
| config: sw |
| split: test |
| args: sw |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.21479210182431807 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # XLS-R-SWAHILI-ASR-CV14 |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: inf |
| - Wer: 0.2148 |
| - Cer: 0.0684 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 10000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
| |:-------------:|:-----:|:-----:|:------:|:---------------:|:------:| |
| | 3.9008 | 0.33 | 400 | 0.2565 | inf | 0.8327 | |
| | 0.5689 | 0.66 | 800 | 0.1306 | inf | 0.4598 | |
| | 0.3838 | 1.0 | 1200 | 0.1130 | inf | 0.3786 | |
| | 0.3054 | 1.33 | 1600 | 0.1032 | inf | 0.3407 | |
| | 0.2877 | 1.66 | 2000 | 0.0976 | inf | 0.3239 | |
| | 0.2698 | 1.99 | 2400 | 0.0952 | inf | 0.3078 | |
| | 0.2285 | 2.32 | 2800 | 0.0956 | inf | 0.3031 | |
| | 0.224 | 2.66 | 3200 | 0.0892 | inf | 0.2861 | |
| | 0.2224 | 2.99 | 3600 | 0.0877 | inf | 0.2809 | |
| | 0.1906 | 3.32 | 4000 | 0.0853 | inf | 0.2748 | |
| | 0.1897 | 3.65 | 4400 | 0.0844 | inf | 0.2707 | |
| | 0.183 | 3.98 | 4800 | 0.0814 | inf | 0.2614 | |
| | 0.1586 | 4.32 | 5200 | 0.0809 | inf | 0.2569 | |
| | 0.162 | 4.65 | 5600 | 0.0782 | inf | 0.2493 | |
| | 0.1548 | 4.98 | 6000 | 0.0772 | inf | 0.2467 | |
| | 0.1364 | 5.31 | 6400 | 0.0782 | inf | 0.2459 | |
| | 0.1344 | 5.64 | 6800 | 0.0760 | inf | 0.2404 | |
| | 0.1301 | 5.98 | 7200 | 0.0738 | inf | 0.2346 | |
| | 0.1165 | 6.31 | 7600 | inf | 0.2321 | 0.0729 | |
| | 0.1142 | 6.64 | 8000 | inf | 0.2266 | 0.0719 | |
| | 0.1103 | 6.97 | 8400 | inf | 0.2229 | 0.0705 | |
| | 0.101 | 7.3 | 8800 | inf | 0.2203 | 0.0699 | |
| | 0.1006 | 7.63 | 9200 | inf | 0.2174 | 0.0692 | |
| | 0.0958 | 7.97 | 9600 | inf | 0.2160 | 0.0688 | |
| | 0.0896 | 8.3 | 10000 | inf | 0.2148 | 0.0684 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.1 |
| - Pytorch 2.2.1 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.2 |
| |
