metadata
library_name: transformers
language:
- fa
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large fa - Mobin Tadbir Sharif
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: fa
split: None
args: 'config: fa, split: test'
metrics:
- name: Wer
type: wer
value: 91.65836687359301
Whisper Large fa - Mobin Tadbir Sharif
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8106
- Wer: 91.6584
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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.581 | 0.0869 | 1000 | 2.5843 | 104.8093 |
| 2.2554 | 0.1738 | 2000 | 2.3093 | 111.6202 |
| 2.1214 | 0.2607 | 3000 | 2.1839 | 105.5556 |
| 2.024 | 0.3477 | 4000 | 2.1036 | 113.6312 |
| 1.9005 | 0.4346 | 5000 | 2.0217 | 135.5618 |
| 1.7344 | 0.5215 | 6000 | 1.8019 | 107.0619 |
| 1.4862 | 0.6084 | 7000 | 1.5560 | 101.7136 |
| 1.253 | 0.6953 | 8000 | 1.3641 | 106.0004 |
| 1.0361 | 0.7822 | 9000 | 1.1275 | 98.4010 |
| 0.8509 | 0.8692 | 10000 | 0.9458 | 97.6069 |
| 0.7212 | 0.9561 | 11000 | 0.8106 | 91.6584 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0