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-new-nnat-10h-caps-ecapa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 21.692502224511777
name: Wer
whisper-new-nnat-10h-caps-ecapa
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: 0.4781
- Wer: 21.6925
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: 0.0001
- train_batch_size: 48
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch_fused 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: 59
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4332 | 0.2995 | 59 | 0.6828 | 31.1806 |
| 0.4937 | 0.5990 | 118 | 0.5383 | 23.9873 |
| 0.3968 | 0.8985 | 177 | 0.5136 | 23.0366 |
| 0.402 | 1.1980 | 236 | 0.5016 | 22.7369 |
| 0.3518 | 1.4975 | 295 | 0.4921 | 21.8517 |
| 0.3556 | 1.7970 | 354 | 0.4859 | 22.0344 |
| 0.3345 | 2.0964 | 413 | 0.4839 | 21.9313 |
| 0.3128 | 2.3959 | 472 | 0.4810 | 21.9220 |
| 0.3074 | 2.6954 | 531 | 0.4791 | 21.7253 |
| 0.3198 | 2.9949 | 590 | 0.4781 | 21.6925 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2