metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-US
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: 0.35360094451003543
whisper-tiny-en-US
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: 0.6166
- Wer Ortho: 0.3504
- Wer: 0.3536
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
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.7658 | 1.7857 | 50 | 0.5871 | 0.3948 | 0.3932 |
| 0.2602 | 3.5714 | 100 | 0.4866 | 0.3504 | 0.3501 |
| 0.0796 | 5.3571 | 150 | 0.5121 | 0.3424 | 0.3453 |
| 0.0316 | 7.1429 | 200 | 0.5443 | 0.3374 | 0.3418 |
| 0.0116 | 8.9286 | 250 | 0.5672 | 0.3202 | 0.3253 |
| 0.0034 | 10.7143 | 300 | 0.5966 | 0.3529 | 0.3566 |
| 0.0026 | 12.5 | 350 | 0.6046 | 0.3541 | 0.3583 |
| 0.002 | 14.2857 | 400 | 0.6098 | 0.3498 | 0.3536 |
| 0.002 | 16.0714 | 450 | 0.6146 | 0.3510 | 0.3542 |
| 0.002 | 17.8571 | 500 | 0.6166 | 0.3504 | 0.3536 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1