metadata
language:
- pa-IN
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Panjabi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: pa-IN
split: test
args: pa-IN
metrics:
- name: Wer
type: wer
value: 36.10043556238791
Whisper Small Panjabi
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: 0.6084
- Wer: 36.1004
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: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.349 | 5.86 | 100 | 0.4664 | 49.1929 |
| 0.0175 | 11.74 | 200 | 0.4633 | 39.1494 |
| 0.0052 | 17.63 | 300 | 0.5317 | 37.7146 |
| 0.0014 | 23.51 | 400 | 0.5521 | 36.4079 |
| 0.0009 | 29.4 | 500 | 0.5731 | 35.4599 |
| 0.0002 | 35.29 | 600 | 0.5806 | 35.6649 |
| 0.0001 | 41.17 | 700 | 0.5933 | 35.7161 |
| 0.0001 | 47.06 | 800 | 0.6016 | 35.9211 |
| 0.0001 | 52.91 | 900 | 0.6067 | 36.0492 |
| 0.0001 | 58.8 | 1000 | 0.6084 | 36.1004 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2