metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
config: en-US
split: train
args: en-US
metrics:
- name: Wer
type: wer
value: 32.99881936245573
whisper-tiny-en
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: 0.8597
- Wer Ortho: 32.7576
- Wer: 32.9988
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: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0007 | 17.2414 | 500 | 0.6479 | 32.3874 | 32.3495 |
| 0.0002 | 34.4828 | 1000 | 0.7071 | 32.8809 | 32.9988 |
| 0.0001 | 51.7241 | 1500 | 0.7428 | 32.7576 | 32.9988 |
| 0.0001 | 68.9655 | 2000 | 0.7709 | 32.6959 | 32.9398 |
| 0.0 | 86.2069 | 2500 | 0.7948 | 32.7576 | 33.0579 |
| 0.0 | 103.4483 | 3000 | 0.8179 | 33.0043 | 33.2349 |
| 0.0 | 120.6897 | 3500 | 0.8392 | 32.9426 | 33.1759 |
| 0.0 | 137.9310 | 4000 | 0.8597 | 32.7576 | 32.9988 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1