| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: alamsher/wav2vec2-large-xlsr-53-common-voice-sw |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - common_voice_17_0 |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: model |
| | results: |
| | - task: |
| | name: Automatic Speech Recognition |
| | type: automatic-speech-recognition |
| | dataset: |
| | name: common_voice_17_0 |
| | type: common_voice_17_0 |
| | config: sw |
| | split: validation |
| | args: sw |
| | metrics: |
| | - name: Wer |
| | type: wer |
| | value: 0.18270008084074374 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # model |
| |
|
| | This model is a fine-tuned version of [alamsher/wav2vec2-large-xlsr-53-common-voice-sw](https://huggingface.co/alamsher/wav2vec2-large-xlsr-53-common-voice-sw) on the common_voice_17_0 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2929 |
| | - Wer: 0.1827 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 15 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-------:|:-----:|:---------------:|:------:| |
| | | 0.2938 | 0.5028 | 500 | 0.3439 | 0.1940 | |
| | | 0.273 | 1.0050 | 1000 | 0.3088 | 0.1923 | |
| | | 0.2327 | 1.5078 | 1500 | 0.3031 | 0.1907 | |
| | | 0.2351 | 2.0101 | 2000 | 0.2877 | 0.1897 | |
| | | 0.2213 | 2.5128 | 2500 | 0.2915 | 0.1889 | |
| | | 0.2172 | 3.0151 | 3000 | 0.2863 | 0.1879 | |
| | | 0.191 | 3.5178 | 3500 | 0.2881 | 0.1880 | |
| | | 0.2048 | 4.0201 | 4000 | 0.2832 | 0.1875 | |
| | | 0.1928 | 4.5229 | 4500 | 0.2825 | 0.1863 | |
| | | 0.1871 | 5.0251 | 5000 | 0.2861 | 0.1863 | |
| | | 0.1856 | 5.5279 | 5500 | 0.2856 | 0.1856 | |
| | | 0.1763 | 6.0302 | 6000 | 0.2854 | 0.1856 | |
| | | 0.1707 | 6.5329 | 6500 | 0.2883 | 0.1853 | |
| | | 0.1714 | 7.0352 | 7000 | 0.2849 | 0.1850 | |
| | | 0.1577 | 7.5380 | 7500 | 0.2875 | 0.1851 | |
| | | 0.162 | 8.0402 | 8000 | 0.2852 | 0.1850 | |
| | | 0.1489 | 8.5430 | 8500 | 0.2911 | 0.1833 | |
| | | 0.1674 | 9.0452 | 9000 | 0.2887 | 0.1826 | |
| | | 0.1818 | 9.5480 | 9500 | 0.2894 | 0.1828 | |
| | | 0.165 | 10.0503 | 10000 | 0.2915 | 0.1830 | |
| | | 0.1715 | 10.5530 | 10500 | 0.2929 | 0.1827 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.52.4 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.2 |
| | |
