metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny
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: 0.22434915773353753
whisper-tiny
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: 0.5913
- Wer Ortho: 0.2340
- Wer: 0.2243
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: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.7357 | 2.0 | 50 | 0.7179 | 0.2947 | 0.2412 |
| 0.2772 | 4.0 | 100 | 0.4758 | 0.2404 | 0.2113 |
| 0.081 | 6.0 | 150 | 0.5069 | 0.2628 | 0.2282 |
| 0.02 | 8.0 | 200 | 0.5289 | 0.2564 | 0.2297 |
| 0.0044 | 10.0 | 250 | 0.5366 | 0.2452 | 0.2251 |
| 0.0018 | 12.0 | 300 | 0.5565 | 0.2404 | 0.2251 |
| 0.0011 | 14.0 | 350 | 0.5668 | 0.2388 | 0.2259 |
| 0.0009 | 16.0 | 400 | 0.5762 | 0.2364 | 0.2251 |
| 0.0007 | 18.0 | 450 | 0.5847 | 0.2348 | 0.2243 |
| 0.0006 | 20.0 | 500 | 0.5913 | 0.2340 | 0.2243 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3