metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: wme_30s_Static_atWall
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 32.088181261481935
wme_30s_Static_atWall
This model is a fine-tuned version of openai/whisper-medium.en on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9135
- Wer: 32.0882
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: 48
- eval_batch_size: 32
- 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: linear
- lr_scheduler_warmup_steps: 42
- training_steps: 420
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 1.5148 | 34.2009 |
| 0.565 | 0.2 | 84 | 0.9564 | 29.4856 |
| 0.4559 | 0.4 | 168 | 0.9294 | 29.7918 |
| 0.2937 | 1.1833 | 252 | 0.9136 | 28.1384 |
| 0.262 | 1.3833 | 336 | 0.9206 | 28.3527 |
| 0.2024 | 2.1667 | 420 | 0.9135 | 32.0882 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1