metadata
language:
- hi
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Aa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: hi
split: test
args: 'config: hi, split: test'
metrics:
- type: wer
value: 32.29069669008719
name: Wer
Whisper Small Hi - Aa
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4719
- Wer: 32.2907
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0921 | 2.4450 | 1000 | 0.2992 | 35.0504 |
| 0.0217 | 4.8900 | 2000 | 0.3543 | 33.5901 |
| 0.0021 | 7.3350 | 3000 | 0.4208 | 32.4896 |
| 0.0003 | 9.7800 | 4000 | 0.4570 | 32.2568 |
| 0.0002 | 12.2249 | 5000 | 0.4719 | 32.2907 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1