--- license: cc-by-nc-4.0 base_model: facebook/mms-1b-all tags: - automatic-speech-recognition - BembaSpeech - mms - generated_from_trainer metrics: - wer model-index: - name: mms-1b-bem-male-sv results: [] --- [Visualize in Weights & Biases](https://wandb.ai/cicasote/huggingface/runs/x8tbh9an) # mms-1b-bem-male-sv This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BEMBASPEECH - BEM dataset. It achieves the following results on the evaluation set: - Loss: 0.1409 - Wer: 0.3498 ## 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: 0.001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 5.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | No log | 0.2183 | 200 | 0.1927 | 0.4257 | | No log | 0.4367 | 400 | 0.1713 | 0.3885 | | 2.0358 | 0.6550 | 600 | 0.1760 | 0.3907 | | 2.0358 | 0.8734 | 800 | 0.1819 | 0.4143 | | 0.519 | 1.0917 | 1000 | 0.1611 | 0.3869 | | 0.519 | 1.3100 | 1200 | 0.1550 | 0.3736 | | 0.519 | 1.5284 | 1400 | 0.1538 | 0.3771 | | 0.4764 | 1.7467 | 1600 | 0.1744 | 0.4176 | | 0.4764 | 1.9651 | 1800 | 0.1598 | 0.3884 | | 0.4501 | 2.1834 | 2000 | 0.1507 | 0.3577 | | 0.4501 | 2.4017 | 2200 | 0.1535 | 0.3763 | | 0.4501 | 2.6201 | 2400 | 0.1502 | 0.3649 | | 0.4422 | 2.8384 | 2600 | 0.1457 | 0.3502 | | 0.4422 | 3.0568 | 2800 | 0.1485 | 0.3580 | | 0.4217 | 3.2751 | 3000 | 0.1480 | 0.3547 | | 0.4217 | 3.4934 | 3200 | 0.1498 | 0.3666 | | 0.4217 | 3.7118 | 3400 | 0.1458 | 0.3494 | | 0.4144 | 3.9301 | 3600 | 0.1427 | 0.3574 | | 0.4144 | 4.1485 | 3800 | 0.1445 | 0.3594 | | 0.3926 | 4.3668 | 4000 | 0.1462 | 0.3666 | | 0.3926 | 4.5852 | 4200 | 0.1432 | 0.3527 | | 0.3926 | 4.8035 | 4400 | 0.1409 | 0.3498 | ### Framework versions - Transformers 4.43.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1