stt / README.md
eolang's picture
Model save
e7db354 verified
metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: stt
    results: []

stt

This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4300
  • Wer Ortho: 21.3276
  • Wer: 14.7093

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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: cosine
  • lr_scheduler_warmup_steps: 50
  • training_steps: 8000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.4135 0.6180 500 0.4069 29.9115 21.6319
0.2036 1.2361 1000 0.3584 25.8738 18.3552
0.1899 1.8541 1500 0.3390 24.0940 16.4814
0.0978 2.4722 2000 0.3406 24.1957 16.8982
0.0584 3.0902 2500 0.3589 22.7718 15.9189
0.0457 3.7083 3000 0.3660 23.3075 15.8580
0.0203 4.3263 3500 0.3762 22.9108 15.7394
0.0193 4.9444 4000 0.3683 22.0192 15.2616
0.0073 5.5624 4500 0.3926 22.5447 15.5801
0.0022 6.1805 5000 0.4065 21.5649 14.9092
0.0022 6.7985 5500 0.4080 21.2835 14.6313
0.0009 7.4166 6000 0.4180 21.2564 14.6415
0.0007 8.0346 6500 0.4244 21.2361 14.6551
0.0006 8.6527 7000 0.4283 21.3276 14.6957
0.0006 9.2707 7500 0.4297 21.3378 14.7059
0.0006 9.8888 8000 0.4300 21.3276 14.7093

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.6.0
  • Tokenizers 0.21.1