metadata
library_name: transformers
language:
- fa
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper large v3 - Mohammad Khosravi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: fa
split: None
args: 'config: fa, split: test'
metrics:
- name: Wer
type: wer
value: 26.865816602611243
Whisper large v3 - Mohammad Khosravi
This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2444
- Wer: 26.8658
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: 4
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1817 | 0.4296 | 1000 | 0.3223 | 35.6097 |
| 0.1224 | 0.8591 | 2000 | 0.2781 | 31.9537 |
| 0.0703 | 1.2887 | 3000 | 0.2761 | 31.3946 |
| 0.057 | 1.7182 | 4000 | 0.2458 | 27.7885 |
| 0.0263 | 2.1478 | 5000 | 0.2444 | 26.8658 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0