metadata
language:
- fa
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Persian Iranian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 fa
type: mozilla-foundation/common_voice_16_0
config: fa
split: test
args: fa
metrics:
- name: Wer
type: wer
value: 58.59649122807018
Whisper Base Persian Iranian
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 fa dataset. It achieves the following results on the evaluation set:
- Loss: 0.7142
- Wer: 58.5965
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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.1086 | 1.02 | 500 | 1.2735 | 85.9444 |
0.8782 | 3.0 | 1000 | 1.0477 | 76.5527 |
0.6726 | 4.02 | 1500 | 0.9506 | 71.8807 |
0.7501 | 6.0 | 2000 | 0.8943 | 69.3890 |
0.6079 | 7.02 | 2500 | 0.8550 | 67.1322 |
0.6592 | 9.0 | 3000 | 0.8239 | 66.2762 |
0.5703 | 10.02 | 3500 | 0.8007 | 63.9907 |
0.5767 | 12.0 | 4000 | 0.7815 | 63.2562 |
0.5098 | 13.02 | 4500 | 0.7671 | 62.1094 |
0.5373 | 15.01 | 5000 | 0.7555 | 61.5551 |
0.4592 | 16.02 | 5500 | 0.7460 | 61.1086 |
0.5032 | 18.01 | 6000 | 0.7376 | 60.5652 |
0.4262 | 19.02 | 6500 | 0.7329 | 60.0792 |
0.4726 | 21.01 | 7000 | 0.7257 | 59.6696 |
0.4043 | 22.02 | 7500 | 0.7237 | 59.3570 |
0.4758 | 24.01 | 8000 | 0.7187 | 59.1098 |
0.412 | 25.02 | 8500 | 0.7173 | 58.8518 |
0.5119 | 27.01 | 9000 | 0.7146 | 58.7276 |
0.4089 | 28.03 | 9500 | 0.7145 | 58.6347 |
0.5186 | 30.01 | 10000 | 0.7142 | 58.5965 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0