metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: da
split: test
args: da
metrics:
- name: Wer
type: wer
value: 16.228300894266177
openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6569
- Wer: 16.2283
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: 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0229 | 7.01 | 1000 | 0.4464 | 16.5124 |
| 0.0072 | 15.0 | 2000 | 0.5081 | 16.1336 |
| 0.0048 | 22.01 | 3000 | 0.5193 | 16.6597 |
| 0.0034 | 30.0 | 4000 | 0.5715 | 16.8964 |
| 0.0005 | 37.01 | 5000 | 0.5998 | 16.4440 |
| 0.0007 | 45.01 | 6000 | 0.5908 | 16.8017 |
| 0.0001 | 53.0 | 7000 | 0.6093 | 16.2336 |
| 0.0001 | 60.01 | 8000 | 0.6405 | 16.3335 |
| 0.0 | 68.0 | 9000 | 0.6524 | 16.2493 |
| 0.0 | 75.01 | 10000 | 0.6569 | 16.2283 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2