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-5h-mmr-ecapa
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JASMIN-CGN
type: jasmin
metrics:
- type: wer
value: 35.10513745141198
name: Wer
whisper-new-nnat-5h-mmr-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: 0.5545
- Wer: 35.1051
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: 62
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9171 | 0.2967 | 62 | 0.7342 | 44.3497 |
| 0.377 | 0.5933 | 124 | 0.6011 | 41.0902 |
| 0.3449 | 0.8900 | 186 | 0.5843 | 42.5420 |
| 0.315 | 1.1866 | 248 | 0.5710 | 39.1186 |
| 0.2988 | 1.4833 | 310 | 0.5689 | 45.5393 |
| 0.2893 | 1.7799 | 372 | 0.5588 | 37.1330 |
| 0.2607 | 2.0766 | 434 | 0.5569 | 36.0230 |
| 0.2532 | 2.3732 | 496 | 0.5575 | 35.7046 |
| 0.2599 | 2.6699 | 558 | 0.5543 | 34.4776 |
| 0.2716 | 2.9665 | 620 | 0.5545 | 35.1051 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2