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---
library_name: peft
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- wft
- whisper
- automatic-speech-recognition
- audio
- speech
- generated_from_trainer
datasets:
- Shamus/multimed_short
metrics:
- wer
model-index:
- name: whisper-BASE-LORA-med
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Shamus/multimed_short
type: Shamus/multimed_short
metrics:
- type: wer
value: 21.47240659965864
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-BASE-LORA-med
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Shamus/multimed_short dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5848
- Wer: 21.4724
- Cer: 12.0240
## 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 OptimizerNames.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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.2829 | 1.0 | 7077 | 0.6521 | 24.4961 | 14.2032 |
| 0.8621 | 2.0 | 14154 | 0.6147 | 24.9126 | 14.5952 |
| 0.3164 | 3.0 | 21231 | 0.5794 | 22.2598 | 12.4891 |
| 0.3039 | 4.0 | 28308 | 0.5678 | 22.0960 | 12.5164 |
| 0.5835 | 5.0 | 35385 | 0.5848 | 21.4724 | 12.0240 |
### Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1 |