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---
library_name: transformers
language:
- en
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- ntnu-smil/lttc-rebalanced-1-split
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-score-5-rebalanced-2
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: ntnu-smil/lttc-rebalanced-1-split
type: ntnu-smil/lttc-rebalanced-1-split
metrics:
- type: wer
value: 36.52802893309223
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-score-5-rebalanced-2
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the ntnu-smil/lttc-rebalanced-1-split dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7199
- Wer: 36.5280
- Cer: 25.0
## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.0489 | 1.0 | 18 | 3.2509 | 37.2514 | 23.4504 |
| 0.1246 | 2.0 | 36 | 3.6744 | 35.6239 | 23.5709 |
| 0.0011 | 3.0 | 54 | 3.6182 | 36.7089 | 22.9855 |
| 0.0075 | 4.0 | 72 | 3.7182 | 37.1609 | 22.6240 |
| 0.0002 | 5.0 | 90 | 3.7643 | 37.7939 | 23.6398 |
| 0.0028 | 6.0 | 108 | 3.6117 | 36.7089 | 23.8809 |
| 0.0003 | 7.0 | 126 | 3.5535 | 36.8897 | 24.6556 |
| 0.0001 | 8.0 | 144 | 3.6586 | 37.7939 | 25.1033 |
| 0.0003 | 9.0 | 162 | 3.6168 | 36.8897 | 24.7934 |
| 0.0001 | 10.0 | 180 | 3.6500 | 37.1609 | 25.1033 |
| 0.0002 | 11.0 | 198 | 3.6934 | 37.4322 | 25.3960 |
| 0.0001 | 12.0 | 216 | 3.6901 | 36.9801 | 25.2410 |
| 0.0001 | 13.0 | 234 | 3.6980 | 36.7993 | 25.2238 |
| 0.0001 | 14.0 | 252 | 3.6990 | 36.9801 | 25.1377 |
| 0.0002 | 15.0 | 270 | 3.7110 | 36.9801 | 25.2755 |
| 0.0001 | 16.0 | 288 | 3.7139 | 36.7993 | 25.1894 |
| 0.0001 | 17.0 | 306 | 3.7175 | 36.7089 | 25.1722 |
| 0.0001 | 18.0 | 324 | 3.7202 | 36.9801 | 25.3444 |
| 0.0001 | 19.0 | 342 | 3.7210 | 36.8897 | 24.9828 |
| 0.0002 | 20.0 | 360 | 3.7199 | 36.5280 | 25.0 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3 |