metadata
language:
- fa
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: anuragshas/whisper-large-v2-hi
model-index:
- name: Whisper_large_Persian
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 fa
type: mozilla-foundation/common_voice_11_0
config: fa
split: test
metrics:
- type: wer
value: 26.367876079171644
name: Wer
Whisper large persian
This model is a fine-tuned version of anuragshas/whisper-large-v2-hi on the mozilla-foundation/common_voice_11_0 fa dataset. It achieves the following results on the evaluation set:
- Loss: 0.3047
- Wer: 26.3679
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: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2948 | 0.19 | 250 | 0.4258 | 35.6023 |
| 0.2443 | 0.39 | 500 | 0.3650 | 30.9747 |
| 0.1956 | 0.58 | 750 | 0.3228 | 28.0196 |
| 0.1715 | 0.78 | 1000 | 0.3047 | 26.3679 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2