metadata
language:
- bn
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Base Bn - Raiyan Ahmed
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: bn
split: None
args: 'config: bn, split: test'
metrics:
- name: Wer
type: wer
value: 33.54106242324475
Whisper Base Bn - Raiyan Ahmed
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2026
- Wer: 33.5411
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: 3.75e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 16000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2369 | 0.6365 | 1000 | 0.2433 | 62.1881 |
| 0.1242 | 1.2731 | 2000 | 0.1734 | 49.4369 |
| 0.1022 | 1.9096 | 3000 | 0.1197 | 39.0531 |
| 0.046 | 2.5461 | 4000 | 0.1067 | 34.5497 |
| 0.0777 | 3.1827 | 5000 | 0.1440 | 43.2194 |
| 0.0649 | 3.8192 | 6000 | 0.1266 | 38.6232 |
| 0.0367 | 4.4558 | 7000 | 0.1288 | 38.0392 |
| 0.0126 | 5.0923 | 8000 | 0.1382 | 35.0226 |
| 0.0108 | 5.7288 | 9000 | 0.1416 | 34.5340 |
| 0.0038 | 6.3654 | 10000 | 0.1611 | 33.3921 |
| 0.0023 | 7.0019 | 11000 | 0.1744 | 33.4875 |
| 0.0133 | 7.6384 | 12000 | 0.1625 | 36.0534 |
| 0.0066 | 8.2750 | 13000 | 0.1801 | 35.3936 |
| 0.004 | 8.9115 | 14000 | 0.1781 | 34.1577 |
| 0.0009 | 9.5481 | 15000 | 0.1918 | 33.6939 |
| 0.0003 | 10.1846 | 16000 | 0.2026 | 33.5411 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1