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: whisper-medium-en-cv-8.0
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: 22.90263319044703
whisper-medium-en-cv-8.0
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: 0.7352
- Wer: 22.9026
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: 375
- training_steps: 2250
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 2.0556 | 32.3025 |
| 0.5507 | 0.1667 | 375 | 0.7920 | 25.9032 |
| 0.3861 | 0.3333 | 750 | 0.7215 | 24.6479 |
| 0.205 | 1.1667 | 1125 | 0.7130 | 22.8108 |
| 0.1431 | 1.3333 | 1500 | 0.7193 | 23.8212 |
| 0.0802 | 2.1667 | 1875 | 0.7302 | 23.5150 |
| 0.0626 | 2.3333 | 2250 | 0.7352 | 22.9026 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1