metadata
language:
- en
license: apache-2.0
base_model: piyushmaharana/outcomes-whisper-tiny-v1.1
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: 1.7139090309822018
OutcomesAI-Whisper-tiny-v1.2
This model is a fine-tuned version of piyushmaharana/outcomes-whisper-tiny-v1.1 on the big-transcript-pronounce dataset. It achieves the following results on the evaluation set:
- Loss: 0.0256
- Wer: 1.7139
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.112 | 2.1645 | 500 | 0.0645 | 5.5784 |
| 0.013 | 4.3290 | 1000 | 0.0310 | 2.3237 |
| 0.0032 | 6.4935 | 1500 | 0.0264 | 1.7798 |
| 0.0012 | 8.6580 | 2000 | 0.0260 | 1.7304 |
| 0.0007 | 10.8225 | 2500 | 0.0257 | 1.7963 |
| 0.0006 | 12.9870 | 3000 | 0.0256 | 1.7139 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1