metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: fine-tuned-Whisper-Tiny-en-US
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: minds14 - en(US)
type: PolyAI/minds14
config: en-US
split: train
args: 'config: en-US, split: test'
metrics:
- name: Wer
type: wer
value: 0.3247210804462713
fine-tuned-Whisper-Tiny-en-US
This model is a fine-tuned version of openai/whisper-tiny on the minds14 - en(US) dataset. It achieves the following results on the evaluation set:
- Loss: 0.7793
- Wer Ortho: 0.3222
- Wer: 0.3247
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 400
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0014 | 17.24 | 500 | 0.5901 | 0.3210 | 0.3188 |
| 0.0003 | 34.48 | 1000 | 0.6579 | 0.3124 | 0.3142 |
| 0.0002 | 51.72 | 1500 | 0.6892 | 0.3143 | 0.3165 |
| 0.0001 | 68.97 | 2000 | 0.7129 | 0.3167 | 0.3194 |
| 0.0001 | 86.21 | 2500 | 0.7330 | 0.3179 | 0.3206 |
| 0.0 | 103.45 | 3000 | 0.7511 | 0.3191 | 0.3218 |
| 0.0 | 120.69 | 3500 | 0.7653 | 0.3179 | 0.3206 |
| 0.0 | 137.93 | 4000 | 0.7793 | 0.3222 | 0.3247 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2