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-maxcos-ecapa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 26.431883107760036
name: Wer
whisper-new-nnat-10h-maxcos-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: 0.5305
- Wer: 26.4319
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: 91
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6936 | 0.2984 | 91 | 0.6340 | 45.6095 |
| 0.3958 | 0.5967 | 182 | 0.5687 | 33.3396 |
| 0.3687 | 0.8951 | 273 | 0.5474 | 28.3426 |
| 0.3232 | 1.1934 | 364 | 0.5466 | 29.8319 |
| 0.2992 | 1.4918 | 455 | 0.5458 | 27.5371 |
| 0.3277 | 1.7902 | 546 | 0.5312 | 26.2352 |
| 0.3002 | 2.0885 | 637 | 0.5286 | 25.6357 |
| 0.2726 | 2.3869 | 728 | 0.5317 | 27.2655 |
| 0.2821 | 2.6852 | 819 | 0.5328 | 26.3991 |
| 0.2643 | 2.9836 | 910 | 0.5305 | 26.4319 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2