metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-polyai-enUS_lower_lr
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: PolyAI/minds14
type: PolyAI/minds14
metrics:
- name: Wer
type: wer
value: 0.38488783943329397
whisper-tiny-polyai-enUS_lower_lr
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: 0.7730
- Wer Ortho: 0.4022
- Wer: 0.3849
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 2.9571 | 3.33 | 50 | 1.9622 | 0.5077 | 0.4050 |
| 0.5131 | 6.67 | 100 | 0.6540 | 0.4152 | 0.3684 |
| 0.2572 | 10.0 | 150 | 0.6091 | 0.3874 | 0.3524 |
| 0.0974 | 13.33 | 200 | 0.6316 | 0.3745 | 0.3442 |
| 0.0405 | 16.67 | 250 | 0.6686 | 0.3917 | 0.3577 |
| 0.0116 | 20.0 | 300 | 0.7097 | 0.4028 | 0.3766 |
| 0.0049 | 23.33 | 350 | 0.7341 | 0.3954 | 0.3743 |
| 0.0032 | 26.67 | 400 | 0.7510 | 0.4065 | 0.3884 |
| 0.0023 | 30.0 | 450 | 0.7607 | 0.3967 | 0.3778 |
| 0.0018 | 33.33 | 500 | 0.7730 | 0.4022 | 0.3849 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0