---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- lord-reso/inbrowser-proctor-dataset
metrics:
- wer
model-index:
- name: Whisper-Small-Inbrowser-Proctor
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Inbrowser Procotor Dataset
      type: lord-reso/inbrowser-proctor-dataset
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 17.075501752150366
---

<!-- 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

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: 0.3099
- Wer: 17.0755

## 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: 8
- 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: 25
- training_steps: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3461        | 0.4545 | 25   | 0.4545          | 26.0433 |
| 0.1902        | 0.9091 | 50   | 0.3309          | 17.4419 |
| 0.1184        | 1.3636 | 75   | 0.3120          | 14.6543 |
| 0.0944        | 1.8182 | 100  | 0.3066          | 16.7251 |
| 0.0632        | 2.2727 | 125  | 0.3046          | 14.8455 |
| 0.0688        | 2.7273 | 150  | 0.3060          | 14.8933 |
| 0.0479        | 3.1818 | 175  | 0.3063          | 17.1074 |
| 0.0515        | 3.6364 | 200  | 0.3081          | 15.4986 |
| 0.0296        | 4.0909 | 225  | 0.3096          | 17.2507 |
| 0.0348        | 4.5455 | 250  | 0.3099          | 17.0755 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1