kbd-asr-colab2

This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1829
  • Wer: 0.3182

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: 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_steps: 100
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7968 0.1871 200 0.4521 0.7382
0.6536 0.3742 400 0.3965 0.7499
0.5989 0.5613 600 0.3850 0.7644
0.5212 0.7484 800 0.3473 0.6373
0.5649 0.9355 1000 0.2951 0.5633
0.4996 1.1225 1200 0.2771 0.4806
0.5247 1.3096 1400 0.2553 0.4592
0.4559 1.4967 1600 0.2537 0.4396
0.5153 1.6838 1800 0.2479 0.4364
0.4622 1.8709 2000 0.2363 0.4251
0.4533 2.0580 2200 0.2280 0.4091
0.4529 2.2451 2400 0.2182 0.4066
0.4453 2.4322 2600 0.2191 0.3902
0.4339 2.6193 2800 0.2135 0.3815
0.4179 2.8064 3000 0.2151 0.3906
0.3983 2.9935 3200 0.2059 0.3725
0.3868 3.1805 3400 0.2058 0.3614
0.3804 3.3676 3600 0.1959 0.3558
0.3934 3.5547 3800 0.2015 0.3555
0.3693 3.7418 4000 0.1995 0.3587
0.3678 3.9289 4200 0.2017 0.3876
0.4097 4.1160 4400 0.1893 0.3355
0.34 4.3031 4600 0.1877 0.3291
0.3553 4.4902 4800 0.1857 0.3222
0.3133 4.6773 5000 0.1839 0.3224
0.3077 4.8644 5200 0.1829 0.3182

Framework versions

  • Transformers 4.50.0.dev0
  • Pytorch 2.5.1+cu121
  • Datasets 3.3.2
  • Tokenizers 0.21.0
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