---
library_name: transformers
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