metadata
language:
- bn
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper tiny bn - Raiyan
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice_13.0
type: mozilla-foundation/common_voice_13_0
config: bn
split: None
args: 'config: bn, split: test'
metrics:
- name: Wer
type: wer
value: 44.349095570431565
Whisper tiny bn - Raiyan
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice_13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1734
- Wer: 44.3491
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: 6e-05
- train_batch_size: 24
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 3000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.261 | 1.0661 | 500 | 0.2417 | 63.3469 |
0.1926 | 2.1322 | 1000 | 0.1941 | 54.3987 |
0.1367 | 3.1983 | 1500 | 0.1729 | 49.3116 |
0.0994 | 4.2644 | 2000 | 0.1622 | 46.2280 |
0.0564 | 5.3305 | 2500 | 0.1669 | 45.0802 |
0.0394 | 6.3966 | 3000 | 0.1734 | 44.3491 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1