metadata
language:
- de
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-fine-tuned-de_learn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: de
split: test[:2000]
args: 'config: german, split: test'
metrics:
- name: Wer
type: wer
value: 19.79678045438977
whisper-fine-tuned-de_learn
This model is a fine-tuned version of whisper-fine-tuned-de_arg_new on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4825
- Wer: 19.7968
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.1169 | 1.6 | 1000 | 0.4126 | 20.2477 |
| 0.0132 | 3.2 | 2000 | 0.4562 | 20.4304 |
| 0.0053 | 4.8 | 3000 | 0.4647 | 20.0480 |
| 0.0016 | 6.4 | 4000 | 0.4775 | 19.8082 |
| 0.0011 | 8.0 | 5000 | 0.4825 | 19.7968 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.13.3