metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-finetune-minds14
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train[450:]
args: en-US
metrics:
- name: Wer
type: wer
value: 0.3382526564344746
whisper-tiny-en-finetune-minds14
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6541
- Wer Ortho: 0.3399
- Wer: 0.3383
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3136 | 3.57 | 100 | 0.4883 | 0.3640 | 0.3524 |
| 0.0417 | 7.14 | 200 | 0.5146 | 0.3560 | 0.3442 |
| 0.0066 | 10.71 | 300 | 0.5736 | 0.3411 | 0.3353 |
| 0.0017 | 14.29 | 400 | 0.6040 | 0.3455 | 0.3418 |
| 0.0013 | 17.86 | 500 | 0.6226 | 0.3393 | 0.3365 |
| 0.0009 | 21.43 | 600 | 0.6352 | 0.3393 | 0.3365 |
| 0.0007 | 25.0 | 700 | 0.6436 | 0.3399 | 0.3371 |
| 0.0006 | 28.57 | 800 | 0.6492 | 0.3399 | 0.3383 |
| 0.0006 | 32.14 | 900 | 0.6530 | 0.3399 | 0.3383 |
| 0.0006 | 35.71 | 1000 | 0.6541 | 0.3399 | 0.3383 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3