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---
library_name: peft
language:
- en
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- JacobLinCool/ami-disfluent
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-verbatim-3-lora
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: JacobLinCool/ami-disfluent
type: JacobLinCool/ami-disfluent
metrics:
- type: wer
value: 7.726913698959442
name: Wer
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-large-v3-turbo-verbatim-3-lora
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the JacobLinCool/ami-disfluent dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1459
- Wer: 7.7269
- Cer: 3.2519
- Decode Runtime: 111.0004
- Wer Runtime: 0.0705
- Cer Runtime: 0.0932
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:--------------:|:-----------:|:-----------:|
| No log | 0 | 0 | 2.2169 | 32.7209 | 17.9205 | 106.5404 | 0.0825 | 0.1203 |
| 0.1681 | 0.1 | 100 | 0.1998 | 9.9454 | 4.1038 | 108.1653 | 0.0730 | 0.0960 |
| 0.1025 | 0.2 | 200 | 0.1693 | 8.6885 | 3.7458 | 109.6779 | 0.0707 | 0.0957 |
| 0.2508 | 0.3 | 300 | 0.1590 | 8.3897 | 3.4931 | 110.3209 | 0.0716 | 0.0947 |
| 0.1446 | 1.088 | 400 | 0.1571 | 8.2626 | 3.4939 | 110.1930 | 0.0718 | 0.0951 |
| 0.1833 | 1.188 | 500 | 0.1505 | 8.0463 | 3.4298 | 110.3821 | 0.0709 | 0.0950 |
| 0.1409 | 1.288 | 600 | 0.1489 | 7.9948 | 3.3401 | 110.6880 | 0.0709 | 0.0939 |
| 0.1184 | 2.076 | 700 | 0.1492 | 7.9124 | 3.3181 | 110.6153 | 0.0728 | 0.0946 |
| 0.1737 | 2.176 | 800 | 0.1468 | 7.8128 | 3.2583 | 110.7120 | 0.0714 | 0.0947 |
| 0.1522 | 2.276 | 900 | 0.1462 | 7.7887 | 3.2604 | 110.7694 | 0.0710 | 0.0937 |
| 0.1077 | 3.064 | 1000 | 0.1459 | 7.7269 | 3.2519 | 111.0004 | 0.0705 | 0.0932 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0 |