---
base_model: openai/whisper-small
datasets:
- lord-reso/inbrowser-proctor-dataset
language:
- en
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper-Small-Inbrowser-Proctor-LORA
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Inbrowser Procotor Dataset
      type: lord-reso/inbrowser-proctor-dataset
      args: 'config: en, split: test'
    metrics:
    - type: wer
      value: 18.158649251353935
      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-Small-Inbrowser-Proctor-LORA

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Inbrowser Procotor Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3646
- Wer: 18.1586

## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7817        | 0.8929 | 25   | 0.7456          | 31.6502 |
| 0.3905        | 1.7857 | 50   | 0.4646          | 29.4043 |
| 0.2194        | 2.6786 | 75   | 0.3988          | 20.3090 |
| 0.1697        | 3.5714 | 100  | 0.3776          | 16.1357 |
| 0.1246        | 4.4643 | 125  | 0.3744          | 18.7639 |
| 0.1062        | 5.3571 | 150  | 0.3698          | 19.9267 |
| 0.0862        | 6.25   | 175  | 0.3698          | 19.9108 |
| 0.0701        | 7.1429 | 200  | 0.3651          | 18.0153 |
| 0.0647        | 8.0357 | 225  | 0.3659          | 18.4613 |
| 0.056         | 8.9286 | 250  | 0.3646          | 18.1586 |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1