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_1.3
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: 27.526025719534598
wme_30s_Static_atWall_1.3
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: 0.9007
- Wer: 27.5260
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: 4e-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: 26
- training_steps: 264
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 1.5148 | 34.2009 |
| 0.8009 | 0.1667 | 44 | 1.0184 | 32.0882 |
| 0.5762 | 0.3333 | 88 | 0.9739 | 29.8836 |
| 0.553 | 0.5 | 132 | 0.9501 | 32.0269 |
| 0.4237 | 1.0038 | 176 | 0.9252 | 29.4550 |
| 0.2473 | 1.1705 | 220 | 0.9069 | 30.1286 |
| 0.1507 | 1.3371 | 264 | 0.9007 | 27.5260 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1