metadata
language:
- hi
license: apache-2.0
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
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 35.74028612545501
Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of Taqwa/whisper-small-hiTaqwa on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3353
- Wer: 35.7403
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: 500
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0762 | 0.31 | 125 | 0.2818 | 33.3573 |
| 0.0653 | 0.61 | 250 | 0.2930 | 33.9584 |
| 0.062 | 0.92 | 375 | 0.3060 | 34.7456 |
| 0.0518 | 1.22 | 500 | 0.3353 | 35.7403 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2