| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - common_voice_14_0 |
| | metrics: |
| | - wer |
| | base_model: facebook/wav2vec2-xls-r-300m |
| | model-index: |
| | - name: XLS-R-LUGANDA-ASR-CV14 |
| | results: |
| | - task: |
| | type: automatic-speech-recognition |
| | name: Automatic Speech Recognition |
| | dataset: |
| | name: common_voice_14_0 |
| | type: common_voice_14_0 |
| | config: lg |
| | split: test |
| | args: lg |
| | metrics: |
| | - type: wer |
| | value: 0.2406197895094572 |
| | name: Wer |
| | --- |
| | |
| | <!-- 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-LUGANDA-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: 0.2406 |
| | - Cer: 0.0537 |
| | |
| | ## 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 | Validation Loss | Wer | Cer | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
| | | 4.24 | 0.18 | 400 | inf | 0.8354 | 0.2170 | |
| | | 0.6124 | 0.36 | 800 | inf | 0.5690 | 0.1360 | |
| | | 0.4411 | 0.54 | 1200 | inf | 0.4746 | 0.1120 | |
| | | 0.3839 | 0.72 | 1600 | inf | 0.4409 | 0.1050 | |
| | | 0.3504 | 0.9 | 2000 | inf | 0.3955 | 0.0943 | |
| | | 0.3214 | 1.08 | 2400 | inf | 0.3678 | 0.0854 | |
| | | 0.2879 | 1.26 | 2800 | inf | 0.3614 | 0.0836 | |
| | | 0.284 | 1.45 | 3200 | inf | 0.3411 | 0.0789 | |
| | | 0.2683 | 1.63 | 3600 | inf | 0.3362 | 0.0767 | |
| | | 0.2572 | 1.81 | 4000 | inf | 0.3241 | 0.0740 | |
| | | 0.2532 | 1.99 | 4400 | inf | 0.3117 | 0.0719 | |
| | | 0.2228 | 2.17 | 4800 | inf | 0.2977 | 0.0677 | |
| | | 0.2143 | 2.35 | 5200 | inf | 0.2969 | 0.0676 | |
| | | 0.211 | 2.53 | 5600 | inf | 0.2918 | 0.0665 | |
| | | 0.2066 | 2.71 | 6000 | inf | 0.2848 | 0.0647 | |
| | | 0.2026 | 2.89 | 6400 | inf | 0.2804 | 0.0637 | |
| | | 0.1898 | 3.07 | 6800 | inf | 0.2744 | 0.0627 | |
| | | 0.1747 | 3.25 | 7200 | inf | 0.2668 | 0.0603 | |
| | | 0.1667 | 3.43 | 7600 | inf | 0.2631 | 0.0597 | |
| | | 0.1639 | 3.61 | 8000 | inf | 0.2558 | 0.0580 | |
| | | 0.1601 | 3.79 | 8400 | inf | 0.2519 | 0.0567 | |
| | | 0.1546 | 3.98 | 8800 | inf | 0.2487 | 0.0554 | |
| | | 0.1395 | 4.16 | 9200 | inf | 0.2449 | 0.0551 | |
| | | 0.1364 | 4.34 | 9600 | inf | 0.2425 | 0.0542 | |
| | | 0.1341 | 4.52 | 10000 | inf | 0.2406 | 0.0537 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.38.1 |
| | - Pytorch 2.2.1 |
| | - Datasets 2.17.0 |
| | - Tokenizers 0.15.2 |
| | |
