metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Hindi - Rishabh Mathur
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: hi
split: test
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 35.90811802476686
Whisper Small Hi - Rishabh Mathur
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3956
- WER: 35.9081
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: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 390
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7731 | 0.9708 | 27 | 0.5895 | 60.3386 |
| 0.4964 | 1.9775 | 55 | 0.4101 | 45.7155 |
| 0.2613 | 2.9843 | 83 | 0.3411 | 40.6360 |
| 0.2032 | 3.9910 | 111 | 0.3155 | 37.3949 |
| 0.1622 | 4.9978 | 139 | 0.3081 | 36.0648 |
| 0.1001 | 5.9685 | 166 | 0.3126 | 35.4418 |
| 0.0826 | 6.9753 | 194 | 0.3265 | 35.4762 |
| 0.0541 | 7.9820 | 222 | 0.3401 | 35.3348 |
| 0.0418 | 8.9888 | 250 | 0.3528 | 35.3921 |
| 0.035 | 9.9955 | 278 | 0.3668 | 35.4380 |
| 0.0245 | 10.9663 | 305 | 0.3783 | 35.6291 |
| 0.0212 | 11.9730 | 333 | 0.3880 | 36.0304 |
| 0.0172 | 12.9798 | 361 | 0.3942 | 35.8240 |
| 0.0159 | 13.9865 | 389 | 0.3956 | 35.9158 |
| 0.0159 | 14.0225 | 390 | 0.3956 | 35.9081 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1