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wav2vec2_300m

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: -1.7265
  • Cer: 2.8268
  • Wer: 1.0

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 300
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer Wer
-2.2058 16.6667 100 -1.7563 2.7979 1.0
-2.2553 33.3333 200 -1.7904 2.8052 1.0
-2.3332 50.0 300 -1.8135 2.8289 1.0
-2.3625 66.6667 400 -1.7726 2.7791 1.0
-2.3912 83.3333 500 -1.7941 2.7467 1.0
-2.4162 100.0 600 -1.7979 2.7745 1.0
-2.4141 116.6667 700 -1.7517 2.7428 1.0
-2.4383 133.3333 800 -1.8364 2.9398 1.0
-2.4441 150.0 900 -1.7691 2.8856 1.0
-2.4518 166.6667 1000 -1.7509 2.7699 1.0
-2.4653 183.3333 1100 -1.7286 2.8175 1.0
-2.4651 200.0 1200 -1.7521 2.7321 1.0
-2.4619 216.6667 1300 -1.6761 2.7655 1.0
-2.4649 233.3333 1400 -1.6887 2.7880 1.0
-2.4863 250.0 1500 -1.7591 2.7745 1.0
-2.472 266.6667 1600 -1.7198 2.7464 1.0
-2.477 283.3333 1700 -1.7385 2.8616 1.0
-2.4708 300.0 1800 -1.7265 2.8268 1.0

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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