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metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: psst-model-8e-1s-difflib
    results: []

psst-model-8e-1s-difflib

This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4445
  • Wer: 0.1554
  • Iu F1: 0.7255
  • Iu Tp: 847
  • Iu Fp: 490
  • Iu Fn: 151

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • 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: 664
  • training_steps: 9480

Training results

Training Loss Epoch Step Validation Loss Wer Iu F1 Iu Tp Iu Fp Iu Fn
0.9633 1.0 1185 0.4920 0.2578 0.5748 461 567 115
0.6300 2.0 2370 0.4784 0.2390 0.7674 442 134 134
0.3400 3.0 3555 0.4964 0.2216 0.7584 449 159 127
0.1584 4.0 4740 0.5594 0.2321 0.7517 451 173 125
0.0592 5.0 5925 0.6092 0.2269 0.7496 455 183 121
0.0264 6.0 7110 0.6907 0.2202 0.7760 452 137 124
0.0101 7.0 8295 0.7329 0.2196 0.7654 429 116 147
0.0033 8.0 9480 0.7761 0.2149 0.7690 446 138 130

Framework versions

  • Transformers 5.6.2
  • Pytorch 2.6.0+cu124
  • Datasets 2.21.0
  • Tokenizers 0.22.2