metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- ntnu-smil/sandi2025-ds
metrics:
- wer
model-index:
- name: whisper-large-v3-sandi-3k-1024-28steps
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: ntnu-smil/sandi2025-ds
type: ntnu-smil/sandi2025-ds
metrics:
- type: wer
value: 78.0237561916606
name: Wer
whisper-large-v3-sandi-3k-1024-28steps
This model is a fine-tuned version of openai/whisper-large-v3 on the ntnu-smil/sandi2025-ds dataset. It achieves the following results on the evaluation set:
- Loss: 1.0370
- Wer: 78.0238
- Cer: 215.7449
- Decode Runtime: 252.2954
- Wer Runtime: 0.1988
- Cer Runtime: 0.4668
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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 28
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime |
|---|---|---|---|---|---|---|---|---|
| 2.6493 | 2.0357 | 7 | 1.3706 | 67.2148 | 209.8014 | 252.1421 | 0.2012 | 0.4813 |
| 1.1778 | 4.0714 | 14 | 1.1881 | 82.9771 | 226.7708 | 259.9550 | 0.1999 | 0.4853 |
| 0.9983 | 6.1071 | 21 | 1.0717 | 79.1953 | 220.4455 | 259.7244 | 0.2083 | 0.4860 |
| 1.9008 | 9.0357 | 28 | 1.0370 | 78.0238 | 215.7449 | 252.2954 | 0.1988 | 0.4668 |
Framework versions
- PEFT 0.15.2
- Transformers 4.48.2
- Pytorch 2.4.1+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1