metadata
language:
- bn
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small bn - Group 4
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: default
split: test
args: 'config: bn, split: test'
metrics:
- name: Wer
type: wer
value: 42.212627219456316
Whisper Small bn - Group 4
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2751
- Wer: 42.2126
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.163 | 1.06 | 500 | 0.2064 | 55.6065 |
| 0.0862 | 2.12 | 1000 | 0.1675 | 47.1869 |
| 0.0475 | 3.18 | 1500 | 0.1696 | 44.8561 |
| 0.0239 | 4.24 | 2000 | 0.1848 | 43.2436 |
| 0.0119 | 5.3 | 2500 | 0.2081 | 43.5608 |
| 0.0058 | 6.36 | 3000 | 0.2262 | 43.0718 |
| 0.0024 | 7.42 | 3500 | 0.2427 | 42.4726 |
| 0.0009 | 8.47 | 4000 | 0.2611 | 42.6356 |
| 0.0005 | 9.53 | 4500 | 0.2709 | 42.3492 |
| 0.0004 | 10.59 | 5000 | 0.2751 | 42.2126 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0