metadata
language:
- hi
base_model: nurzhanit/whisper-enhanced-ml
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
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: None
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 0.4761904761904762
Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of nurzhanit/whisper-enhanced-ml on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0019
- Wer: 0.4762
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: 50
- training_steps: 300
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2599 | 10.0 | 50 | 0.0325 | 5.7937 |
| 0.0078 | 20.0 | 100 | 0.0026 | 0.4762 |
| 0.004 | 30.0 | 150 | 0.0020 | 0.4762 |
| 0.002 | 40.0 | 200 | 0.0020 | 0.4762 |
| 0.0018 | 50.0 | 250 | 0.0019 | 0.4762 |
| 0.0018 | 60.0 | 300 | 0.0019 | 0.4762 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1