metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- common_voice_1_0
metrics:
- wer
model-index:
- name: whisper-tiny-en_v9
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_1_0
type: common_voice_1_0
config: en
split: test[:2427]
args: en
metrics:
- name: Wer
type: wer
value: 20.715392198281933
whisper-tiny-en_v9
This model is a fine-tuned version of openai/whisper-tiny.en on the common_voice_1_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6704
- Wer Ortho: 29.3851
- Wer: 20.7154
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.2787 | 0.1647 | 100 | 0.6732 | 29.2789 | 20.7342 |
| 0.2382 | 0.3295 | 200 | 0.6746 | 29.2306 | 20.6731 |
| 0.2696 | 0.4942 | 300 | 0.6757 | 29.1196 | 20.5793 |
| 0.254 | 0.6590 | 400 | 0.6745 | 29.3223 | 20.6638 |
| 0.2935 | 0.8237 | 500 | 0.6737 | 29.3658 | 20.6591 |
| 0.2757 | 0.9885 | 600 | 0.6704 | 29.3851 | 20.7154 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.6
- Tokenizers 0.21.1