metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: multilingual-whisper-v3-scripted
results: []
multilingual-whisper-v3-scripted
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4568
- Wer: 0.5008
- Cer: 0.1871
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.8035 | 0.25 | 500 | 0.6861 | 0.6772 | 0.2742 |
| 0.427 | 0.5 | 1000 | 0.5404 | 0.4711 | 0.1497 |
| 0.6455 | 0.75 | 1500 | 0.4845 | 0.5254 | 0.2012 |
| 0.2086 | 1.0 | 2000 | 0.4568 | 0.5008 | 0.1871 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4