metadata
library_name: transformers
language:
- bn
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny Bn - Lohitava Ghosh
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: 63.43184134200831
Whisper Tiny Bn - Lohitava Ghosh
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2394
- Wer: 63.4318
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3354 | 0.6365 | 1000 | 0.3555 | 77.6737 |
| 0.2373 | 1.2731 | 2000 | 0.2772 | 69.6010 |
| 0.2246 | 1.9096 | 3000 | 0.2479 | 65.2452 |
| 0.2028 | 2.5461 | 4000 | 0.2394 | 63.4318 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.1
- Tokenizers 0.21.0