---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- chris_W/dataset
model-index:
- name: Whisper-Small-dadirri
  results: []
---

<!-- 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-dadirri

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the hearing voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0231

## 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: 400
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.52  | 50   | 3.0035          |
| 4.521         | 1.03  | 100  | 1.4394          |
| 4.521         | 1.55  | 150  | 2.7847          |
| 1.8786        | 2.06  | 200  | 0.4913          |
| 1.8786        | 2.58  | 250  | 0.0458          |
| 0.0755        | 3.09  | 300  | 0.0379          |
| 0.0755        | 3.61  | 350  | 0.0285          |
| 0.0126        | 4.12  | 400  | 0.0231          |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.0.1+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2