--- license: apache-2.0 tags: - generated_from_trainer datasets: - filipino_voice model-index: - name: english-filipino-wav2vec2-l-xls-r-test-02 results: [] --- # english-filipino-wav2vec2-l-xls-r-test-02 This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the filipino_voice dataset. It achieves the following results on the evaluation set: - Loss: 0.4561 - Wer: 0.2632 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 40 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 3.1707 | 2.09 | 400 | 0.8006 | 0.8224 | | 0.4801 | 4.19 | 800 | 0.3363 | 0.4329 | | 0.2541 | 6.28 | 1200 | 0.3365 | 0.3676 | | 0.1851 | 8.38 | 1600 | 0.3485 | 0.3739 | | 0.1408 | 10.47 | 2000 | 0.3628 | 0.3420 | | 0.1098 | 12.57 | 2400 | 0.3979 | 0.3277 | | 0.1019 | 14.66 | 2800 | 0.4031 | 0.2896 | | 0.0887 | 16.75 | 3200 | 0.3977 | 0.3024 | | 0.0798 | 18.85 | 3600 | 0.3959 | 0.3129 | | 0.0671 | 20.94 | 4000 | 0.4489 | 0.3241 | | 0.0633 | 23.04 | 4400 | 0.4455 | 0.3026 | | 0.055 | 25.13 | 4800 | 0.4668 | 0.2910 | | 0.0523 | 27.23 | 5200 | 0.4670 | 0.2960 | | 0.0468 | 29.32 | 5600 | 0.4536 | 0.2781 | | 0.0392 | 31.41 | 6000 | 0.4612 | 0.2860 | | 0.0381 | 33.51 | 6400 | 0.4651 | 0.2841 | | 0.034 | 35.6 | 6800 | 0.4723 | 0.2716 | | 0.0315 | 37.7 | 7200 | 0.4546 | 0.2642 | | 0.0294 | 39.79 | 7600 | 0.4561 | 0.2632 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.0+cu113 - Datasets 1.18.3 - Tokenizers 0.10.3