Serialtechlab / mms-1b-dhivehi-finetuned

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Model's Last Updated: January 30 2026
automatic-speech-recognition

Introduction of mms-1b-dhivehi-finetuned

Model Details of mms-1b-dhivehi-finetuned

mms-1b-dhivehi-finetuned

This model is a fine-tuned version of facebook/mms-1b-all on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4735
  • Wer: 0.5684
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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 5
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
0.8561 0.4813 200 0.6015 0.5990
0.7882 0.9627 400 0.5385 0.5823
0.7576 1.4428 600 0.5117 0.5758
0.75 1.9242 800 0.4980 0.5754
0.7907 2.4043 1000 0.4895 0.5727
0.7268 2.8857 1200 0.4817 0.5732
0.6884 3.3658 1400 0.4788 0.5692
0.7694 3.8472 1600 0.4750 0.5709
0.7055 4.3273 1800 0.4735 0.5684
0.8217 4.8087 2000 0.4721 0.5692
Framework versions
  • Transformers 4.57.3
  • Pytorch 2.9.1+cu128
  • Datasets 4.4.2
  • Tokenizers 0.22.1

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