metadata
language:
- da
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Danish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: da
split: test
args: da
metrics:
- name: Wer
type: wer
value: 15.36559705418201
Whisper Medium Danish
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 da dataset. It achieves the following results on the evaluation set:
- Loss: 0.5759
- Wer: 15.3656
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.016 | 7.58 | 1000 | 0.4492 | 15.7391 |
| 0.0014 | 15.15 | 2000 | 0.5306 | 15.4550 |
| 0.0004 | 22.73 | 3000 | 0.5759 | 15.3656 |
| 0.0003 | 30.3 | 4000 | 0.5981 | 15.4655 |
| 0.0002 | 37.88 | 5000 | 0.6072 | 15.5076 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2