metadata
language:
- en
license: apache-2.0
base_model: piyushmaharana/outcomes-whisper-tiny-v1
tags:
- generated_from_trainer
datasets:
- ray-outcomes-ai/big-transcript-pronounce
metrics:
- wer
model-index:
- name: OutcomesAI-Whisper-tiny-v1.2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: big-transcript-pronounce
type: ray-outcomes-ai/big-transcript-pronounce
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 2.8199566160520604
OutcomesAI-Whisper-tiny-v1.2
This model is a fine-tuned version of piyushmaharana/outcomes-whisper-tiny-v1 on the big-transcript-pronounce dataset. It achieves the following results on the evaluation set:
- Loss: 0.0602
- Wer: 2.8200
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: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0401 | 12.5 | 100 | 0.0998 | 5.4230 |
| 0.0006 | 25.0 | 200 | 0.0777 | 6.5076 |
| 0.0003 | 37.5 | 300 | 0.0723 | 4.1215 |
| 0.0002 | 50.0 | 400 | 0.0691 | 3.4707 |
| 0.0001 | 62.5 | 500 | 0.0669 | 3.2538 |
| 0.0001 | 75.0 | 600 | 0.0656 | 3.0369 |
| 0.0001 | 87.5 | 700 | 0.0646 | 3.2538 |
| 0.0001 | 100.0 | 800 | 0.0635 | 3.4707 |
| 0.0001 | 112.5 | 900 | 0.0628 | 3.4707 |
| 0.0001 | 125.0 | 1000 | 0.0624 | 3.4707 |
| 0.0001 | 137.5 | 1100 | 0.0619 | 3.4707 |
| 0.0001 | 150.0 | 1200 | 0.0614 | 2.8200 |
| 0.0001 | 162.5 | 1300 | 0.0613 | 3.2538 |
| 0.0 | 175.0 | 1400 | 0.0609 | 3.2538 |
| 0.0 | 187.5 | 1500 | 0.0607 | 3.2538 |
| 0.0 | 200.0 | 1600 | 0.0606 | 3.2538 |
| 0.0 | 212.5 | 1700 | 0.0604 | 3.2538 |
| 0.0 | 225.0 | 1800 | 0.0605 | 3.4707 |
| 0.0 | 237.5 | 1900 | 0.0603 | 3.2538 |
| 0.0 | 250.0 | 2000 | 0.0602 | 2.8200 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1