---
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: 16.948072634597004
---

<!-- 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: 0.3093
- Wer: 16.9481

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2855        | 0.4545 | 25   | 0.4320          | 24.4186 |
| 0.1728        | 0.9091 | 50   | 0.3271          | 17.4896 |
| 0.0925        | 1.3636 | 75   | 0.3101          | 14.5428 |
| 0.1021        | 1.8182 | 100  | 0.3059          | 16.8366 |
| 0.054         | 2.2727 | 125  | 0.3039          | 15.1641 |
| 0.083         | 2.7273 | 150  | 0.3050          | 14.6703 |
| 0.0355        | 3.1818 | 175  | 0.3055          | 14.7818 |
| 0.0502        | 3.6364 | 200  | 0.3074          | 15.6897 |
| 0.0287        | 4.0909 | 225  | 0.3089          | 17.0596 |
| 0.0347        | 4.5455 | 250  | 0.3093          | 16.9481 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.2.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0