metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-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: 0.3370720188902007
whisper-tiny-finetuned-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: 0.5953
- Wer Ortho: 0.3516
- Wer: 0.3371
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: 500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
3.9735 | 0.89 | 25 | 2.8501 | 0.5281 | 0.3979 |
1.8774 | 1.79 | 50 | 0.8237 | 0.4405 | 0.4067 |
0.53 | 2.68 | 75 | 0.5823 | 0.3874 | 0.3695 |
0.2962 | 3.57 | 100 | 0.5374 | 0.3726 | 0.3642 |
0.1982 | 4.46 | 125 | 0.5273 | 0.3658 | 0.3571 |
0.1361 | 5.36 | 150 | 0.5435 | 0.3701 | 0.3548 |
0.0711 | 6.25 | 175 | 0.5489 | 0.3609 | 0.3483 |
0.0387 | 7.14 | 200 | 0.5826 | 0.3664 | 0.3566 |
0.0221 | 8.04 | 225 | 0.5953 | 0.3516 | 0.3371 |
0.0123 | 8.93 | 250 | 0.6145 | 0.3510 | 0.3418 |
0.0061 | 9.82 | 275 | 0.6406 | 0.3597 | 0.3542 |
0.0041 | 10.71 | 300 | 0.6311 | 0.3479 | 0.3406 |
0.003 | 11.61 | 325 | 0.6513 | 0.3701 | 0.3619 |
0.0019 | 12.5 | 350 | 0.6630 | 0.3652 | 0.3613 |
0.0025 | 13.39 | 375 | 0.6672 | 0.3634 | 0.3601 |
0.0023 | 14.29 | 400 | 0.6738 | 0.3442 | 0.3418 |
0.0011 | 15.18 | 425 | 0.6746 | 0.3461 | 0.3436 |
0.0012 | 16.07 | 450 | 0.6788 | 0.3442 | 0.3430 |
0.0013 | 16.96 | 475 | 0.6865 | 0.3448 | 0.3447 |
0.0009 | 17.86 | 500 | 0.6921 | 0.3467 | 0.3459 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0