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-20h-random-seed2025
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 20.694984311337986
name: Wer
whisper-new-nnat-20h-random-seed2025
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: 0.4691
- Wer: 20.6950
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: 45
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8351 | 0.3 | 45 | 0.8048 | 39.6806 |
| 0.4512 | 0.6 | 90 | 0.5502 | 24.4649 |
| 0.4241 | 0.9 | 135 | 0.5124 | 23.5611 |
| 0.3697 | 1.2 | 180 | 0.4979 | 22.1374 |
| 0.3582 | 1.5 | 225 | 0.4848 | 21.3928 |
| 0.363 | 1.8 | 270 | 0.4774 | 21.5942 |
| 0.3568 | 2.1 | 315 | 0.4744 | 20.7886 |
| 0.3357 | 2.4 | 360 | 0.4710 | 20.6669 |
| 0.3389 | 2.7 | 405 | 0.4697 | 20.8402 |
| 0.338 | 3.0 | 450 | 0.4691 | 20.6950 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2