---
language:
- eng
tags:
- generated_from_trainer
base_model: openai/whisper-small-2000
datasets:
- Kaggle/transcription_audio
metrics:
- wer
model-index:
- name: Whisper Small Eng - noursene
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: medical audio trascription
      type: Kaggle/transcription_audio
      args: 'config: eng'
    metrics:
    - type: wer
      value: 10.536550234065539
      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 Eng - noursene

This model is a fine-tuned version of [openai/whisper-small-2000](https://huggingface.co/openai/whisper-small-2000) on the medical audio trascription dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1612
- Wer: 10.5366

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.191         | 3.0257  | 500  | 0.2308          | 14.0727 |
| 0.0375        | 6.0514  | 1000 | 0.1570          | 10.9975 |
| 0.0045        | 9.0772  | 1500 | 0.1594          | 10.7598 |
| 0.0029        | 12.1029 | 2000 | 0.1612          | 10.5366 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1