metadata
license: apache-2.0
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: 0.3541912632821724
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: 0.6875
- Wer Ortho: 0.3745
- Wer: 0.3542
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: linear
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.6838 | 1.79 | 50 | 0.6522 | 0.4028 | 0.3613 |
| 0.2778 | 3.57 | 100 | 0.5727 | 0.3880 | 0.3589 |
| 0.1313 | 5.36 | 150 | 0.5870 | 0.3794 | 0.3501 |
| 0.0539 | 7.14 | 200 | 0.6080 | 0.3726 | 0.3471 |
| 0.022 | 8.93 | 250 | 0.6380 | 0.3745 | 0.3477 |
| 0.0095 | 10.71 | 300 | 0.6629 | 0.3843 | 0.3595 |
| 0.0049 | 12.5 | 350 | 0.6715 | 0.3819 | 0.3583 |
| 0.0036 | 14.29 | 400 | 0.6811 | 0.3825 | 0.3595 |
| 0.0032 | 16.07 | 450 | 0.6858 | 0.3757 | 0.3554 |
| 0.0029 | 17.86 | 500 | 0.6875 | 0.3745 | 0.3542 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3