---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- medical_speech_transcription
metrics:
- wer
model-index:
- name: whisper_fine_tune_Nataraj
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Medical Speech, Transcription, and Intent
      type: medical_speech_transcription
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 12.673707615341856
---

<!-- 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_fine_tune_Nataraj

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Medical Speech, Transcription, and Intent dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1956
- Wer: 12.6737

## 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: 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: 100
- training_steps: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5559        | 0.2825 | 100  | 0.5252          | 15.9811 |
| 0.1575        | 0.5650 | 200  | 0.2096          | 11.5990 |
| 0.1228        | 0.8475 | 300  | 0.2005          | 11.1729 |
| 0.0528        | 1.1299 | 400  | 0.1967          | 11.6732 |
| 0.0402        | 1.4124 | 500  | 0.1960          | 12.3680 |
| 0.0583        | 1.6949 | 600  | 0.1956          | 12.6737 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1