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-minds14
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: 0.36068476977567887
whisper-tiny-PolyAI-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: 0.5565
- Wer Ortho: 0.5120
- Wer: 0.3607
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-07
- train_batch_size: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|
| 2.3523 | 71.43 | 500 | 2.3552 | 0.6089 | 0.4067 |
| 1.1267 | 142.86 | 1000 | 1.2038 | 0.5922 | 0.4132 |
| 0.5363 | 214.29 | 1500 | 0.7055 | 0.5694 | 0.4014 |
| 0.3846 | 285.71 | 2000 | 0.6171 | 0.5490 | 0.4008 |
| 0.304 | 357.14 | 2500 | 0.5816 | 0.5379 | 0.3890 |
| 0.2428 | 428.57 | 3000 | 0.5644 | 0.5182 | 0.3713 |
| 0.1922 | 500.0 | 3500 | 0.5570 | 0.5139 | 0.3666 |
| 0.1499 | 571.43 | 4000 | 0.5565 | 0.5120 | 0.3607 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1