metadata
library_name: peft
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- base_model:adapter:openai/whisper-large-v2
- lora
- transformers
datasets:
- jasmin
- jasmin-cgn
metrics:
- wer
model-index:
- name: whisper-audeering-classifier
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 35.357466366960786
name: Wer
whisper-audeering-classifier
This model is a fine-tuned version of openai/whisper-large-v2 on the JASMIN-CGN dataset. It achieves the following results on the evaluation set:
- Loss: 0.9865
- Wer: 35.3575
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: 48
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 18
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.07 | 0.1613 | 10 | 1.2246 | 37.8233 |
| 1.0062 | 0.3226 | 20 | 1.2108 | 37.7193 |
| 1.023 | 0.4839 | 30 | 1.1929 | 37.3268 |
| 1.0902 | 0.6452 | 40 | 1.1739 | 37.3872 |
| 1.0716 | 0.8065 | 50 | 1.1540 | 37.1255 |
| 0.9588 | 0.9677 | 60 | 1.1339 | 36.7732 |
| 1.0063 | 1.1290 | 70 | 1.1152 | 36.3673 |
| 0.9921 | 1.2903 | 80 | 1.0970 | 36.0553 |
| 0.9091 | 1.4516 | 90 | 1.0795 | 35.9211 |
| 0.9646 | 1.6129 | 100 | 1.0622 | 35.7601 |
| 0.8876 | 1.7742 | 110 | 1.0463 | 35.6594 |
| 0.8532 | 1.9355 | 120 | 1.0320 | 35.4447 |
| 0.8725 | 2.0968 | 130 | 1.0196 | 35.2870 |
| 0.8831 | 2.2581 | 140 | 1.0095 | 35.3675 |
| 0.8586 | 2.4194 | 150 | 1.0007 | 35.3776 |
| 0.8097 | 2.5806 | 160 | 0.9938 | 35.3004 |
| 0.8906 | 2.7419 | 170 | 0.9890 | 35.6561 |
| 0.8542 | 2.9032 | 180 | 0.9865 | 35.3575 |
Framework versions
- PEFT 0.16.0
- Transformers 4.57.3
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.22.2