metadata
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hindi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 hi
type: mozilla-foundation/common_voice_11_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 22.429210134128166
Whisper Small Hindi
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 hi dataset. It achieves the following results on the evaluation set:
- Loss: 0.6260
- Wer: 22.4292
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: 7e-06
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0176 | 7.01 | 500 | 0.4165 | 22.5066 |
| 0.0015 | 14.01 | 1000 | 0.5186 | 22.2573 |
| 0.0004 | 21.02 | 1500 | 0.5741 | 22.2401 |
| 0.0002 | 28.02 | 2000 | 0.6025 | 22.3834 |
| 0.0002 | 36.01 | 2500 | 0.6197 | 22.3977 |
| 0.0002 | 43.01 | 3000 | 0.6260 | 22.4292 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2