metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en_US-test-finetuned
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: 0.26380766731643923
whisper-tiny-minds14-en_US-test-finetuned
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: 1.0871
- Wer Ortho: 26.8342
- Wer: 0.2638
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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0021 | 17.86 | 500 | 0.7863 | 26.6304 | 0.2534 |
| 0.0002 | 35.71 | 1000 | 0.8689 | 26.7663 | 0.2612 |
| 0.0001 | 53.57 | 1500 | 0.9230 | 27.2418 | 0.2664 |
| 0.0001 | 71.43 | 2000 | 0.9637 | 27.1739 | 0.2664 |
| 0.0 | 89.29 | 2500 | 0.9977 | 26.9022 | 0.2638 |
| 0.0 | 107.14 | 3000 | 1.0277 | 27.1739 | 0.2664 |
| 0.0 | 125.0 | 3500 | 1.0571 | 27.1739 | 0.2671 |
| 0.0 | 142.86 | 4000 | 1.0871 | 26.8342 | 0.2638 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2