github dev branch commit

MSP-AVSR

This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1193
  • Wer: 0.1736

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: 32
  • eval_batch_size: 32
  • seed: 42
  • 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: cosine
  • lr_scheduler_warmup_steps: 1000.0
  • training_steps: 30000

Training results

Training Loss Epoch Step Validation Loss Wer
2.2821 0.0333 1000 1.5690 0.2983
2.1664 0.0667 2000 1.3053 0.2234
2.0936 0.1 3000 1.1193 0.1736
2.2092 0.1333 4000 1.2822 0.2420
2.3215 0.1667 5000 1.4375 0.2676
2.0802 0.2 6000 1.3366 0.2295
2.0530 0.2333 7000 1.2210 0.1985
2.1923 0.2667 8000 1.3655 0.2465
2.1158 0.3 9000 1.4065 0.2484
2.0377 0.3333 10000 1.4430 0.2271
2.0040 0.3667 11000 1.3231 0.2188
1.9140 0.4 12000 1.5497 0.2668
2.1310 0.4333 13000 1.1773 0.1909
2.0774 0.4667 14000 1.1900 0.1888
1.8577 0.5 15000 1.4826 0.2567
1.8542 0.5333 16000 1.3038 0.2196
1.9256 0.5667 17000 1.1100 0.1767
2.0081 0.6 18000 1.3671 0.2258
1.8983 0.6333 19000 1.2541 0.2035
1.8399 0.6667 20000 1.2768 0.2127
1.9230 0.0333 21000 1.3529 0.2279
1.7808 0.0667 22000 1.3944 0.2262
1.8058 0.1 23000 1.2840 0.2044
1.8971 0.1333 24000 1.2563 0.2056
2.0928 0.1667 25000 1.2498 0.2054
1.8353 0.2 26000 1.2187 0.1997
1.8451 0.2333 27000 1.2304 0.1999
2.0854 0.2667 28000 1.2552 0.2079
1.9424 0.3 29000 1.2496 0.2042
1.8996 0.3333 30000 1.2481 0.2046

Framework versions

  • Transformers 5.10.2
  • Pytorch 2.10.0+rocm7.2.4.git3d3aa833
  • Datasets 4.0.0
  • Tokenizers 0.22.2
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