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torgo_xlsr_finetune_F04

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4132
  • Wer: 0.2275

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Wer
3.4699 0.85 1000 3.2861 1.0
2.1971 1.69 2000 2.0008 0.8514
0.9545 2.54 3000 1.4512 0.6358
0.6665 3.39 4000 1.4047 0.5008
0.5094 4.24 5000 1.3973 0.4457
0.4719 5.08 6000 1.4290 0.4066
0.4183 5.93 7000 1.4807 0.3761
0.3525 6.78 8000 1.5710 0.3667
0.3112 7.63 9000 1.4555 0.3268
0.2876 8.47 10000 1.4537 0.2988
0.2321 9.32 11000 1.6268 0.3200
0.2456 10.17 12000 1.3804 0.2852
0.2376 11.02 13000 1.6112 0.3141
0.2169 11.86 14000 1.4480 0.2988
0.2106 12.71 15000 1.6790 0.2929
0.2055 13.56 16000 1.5383 0.2963
0.1601 14.41 17000 1.4142 0.2555
0.1631 15.25 18000 1.5318 0.2470
0.1481 16.1 19000 1.6078 0.2453
0.1374 16.95 20000 1.3588 0.2360
0.1349 17.8 21000 1.3788 0.2309
0.1284 18.64 22000 1.4818 0.2326
0.1328 19.49 23000 1.4132 0.2275

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.13.3
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