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Training completed - WER: 0.3577
4558a61 verified
metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: throatmic_subvocalization_whisper_small
    results: []

throatmic_subvocalization_whisper_small

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

  • Loss: 0.8621
  • Wer: 0.3855

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-06
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Use 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: 50
  • training_steps: 800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.1486 0.4464 25 3.9859 0.8564
3.0886 0.8929 50 2.1745 0.7057
1.7689 1.3393 75 1.7727 0.4748
1.4945 1.7857 100 1.5883 0.4243
1.3174 2.2321 125 1.4747 0.3946
1.082 2.6786 150 1.4101 0.3816
0.967 3.125 175 1.3374 0.3797
0.7866 3.5714 200 1.2746 0.3700
0.6628 4.0179 225 1.0417 0.3784
0.2359 4.4643 250 0.7904 0.3577
0.1835 4.9107 275 0.7902 0.3571
0.1051 5.3571 300 0.8173 0.3726
0.1088 5.8036 325 0.8255 0.3674
0.0894 6.25 350 0.8310 0.3603
0.0683 6.6964 375 0.8385 0.3726
0.051 7.1429 400 0.8621 0.3855

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.6.0+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0