metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
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: hi
split: None
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 32.984847202234825
Whisper Small Hi - Sanchit Gandhi
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: 0.4377
- Wer: 32.9848
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: 32
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.0 | 1 | 2.2652 | 86.7857 |
| 0.1858 | 1.22 | 500 | 0.3301 | 39.7317 |
| 0.0881 | 2.44 | 1000 | 0.2966 | 34.9065 |
| 0.0457 | 3.67 | 1500 | 0.3160 | 33.8695 |
| 0.0195 | 4.89 | 2000 | 0.3571 | 33.9287 |
| 0.0047 | 6.11 | 2500 | 0.3913 | 33.4843 |
| 0.0014 | 7.33 | 3000 | 0.4186 | 32.9637 |
| 0.0005 | 8.56 | 3500 | 0.4286 | 33.0737 |
| 0.0005 | 9.78 | 4000 | 0.4377 | 32.9848 |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2