metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 14.119648426424725
openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2376
- Wer: 14.1196
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: 6e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.443 | 0.06 | 500 | 0.5037 | 37.4296 |
| 0.4196 | 0.12 | 1000 | 0.4010 | 28.9137 |
| 0.2823 | 0.19 | 1500 | 0.3453 | 24.6851 |
| 0.2551 | 0.25 | 2000 | 0.3164 | 22.5789 |
| 0.206 | 0.31 | 2500 | 0.2902 | 19.7922 |
| 0.2327 | 0.38 | 3000 | 0.2707 | 18.9356 |
| 0.1416 | 1.03 | 3500 | 0.2566 | 17.6921 |
| 0.0998 | 1.09 | 4000 | 0.2551 | 16.8213 |
| 0.095 | 1.15 | 4500 | 0.2511 | 16.3899 |
| 0.0971 | 1.21 | 5000 | 0.2415 | 15.5393 |
| 0.0964 | 1.28 | 5500 | 0.2336 | 15.1707 |
| 0.072 | 1.34 | 6000 | 0.2353 | 14.7596 |
| 0.0658 | 1.4 | 6500 | 0.2340 | 14.6766 |
| 0.033 | 2.05 | 7000 | 0.2349 | 14.3768 |
| 0.0288 | 2.11 | 7500 | 0.2371 | 14.1865 |
| 0.0352 | 2.18 | 8000 | 0.2376 | 14.1196 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2