metadata
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small dysarthric Dutch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: data/copas copas-full
type: data/copas
config: copas-full
split: test
args: copas-full
metrics:
- name: Wer
type: wer
value: 24.555998550199348
Whisper Small dysarthric Dutch
This model is a fine-tuned version of qmeeus/whisper-small-nl on the data/copas copas-full dataset. It achieves the following results on the evaluation set:
- Loss: 0.4242
- Wer: 24.5560
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: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.3363 | 2.02 | 500 | 0.3762 | 29.7934 |
| 0.0945 | 5.02 | 1000 | 0.3418 | 27.6912 |
| 0.0332 | 8.01 | 1500 | 0.3353 | 26.1689 |
| 0.0147 | 11.01 | 2000 | 0.3476 | 26.1327 |
| 0.0071 | 14.01 | 2500 | 0.3623 | 25.9333 |
| 0.0034 | 17.01 | 3000 | 0.3789 | 25.2084 |
| 0.0024 | 20.01 | 3500 | 0.3827 | 24.8641 |
| 0.0026 | 23.01 | 4000 | 0.3877 | 25.3171 |
| 0.0021 | 26.01 | 4500 | 0.3933 | 25.4259 |
| 0.0014 | 29.01 | 5000 | 0.3941 | 25.0997 |
| 0.0008 | 32.01 | 5500 | 0.4014 | 25.0997 |
| 0.0004 | 35.01 | 6000 | 0.4035 | 24.8278 |
| 0.0003 | 38.01 | 6500 | 0.4080 | 24.9184 |
| 0.0003 | 41.01 | 7000 | 0.4120 | 24.8097 |
| 0.0002 | 44.01 | 7500 | 0.4151 | 24.6104 |
| 0.0002 | 47.01 | 8000 | 0.4176 | 24.3929 |
| 0.0002 | 50.01 | 8500 | 0.4200 | 24.5198 |
| 0.0001 | 53.0 | 9000 | 0.4230 | 24.5198 |
| 0.0001 | 56.0 | 9500 | 0.4252 | 24.4291 |
| 0.0001 | 59.0 | 10000 | 0.4242 | 24.5560 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1