---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- wwwtwwwt/fineaudio-ArtCreativity
metrics:
- wer
model-index:
- name: Whisper Tiny En - ArtCreativity - Photography Tips
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fineaudio-ArtCreativity-Photography Tips
      type: wwwtwwwt/fineaudio-ArtCreativity
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 38.063369778089054
---

<!-- 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 Tiny En - ArtCreativity - Photography Tips

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fineaudio-ArtCreativity-Photography Tips dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7296
- Wer: 38.0634

## 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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7998        | 0.7199 | 1000 | 0.8235          | 49.0292 |
| 0.5335        | 1.4399 | 2000 | 0.7543          | 42.1397 |
| 0.4172        | 2.1598 | 3000 | 0.7355          | 40.0646 |
| 0.3939        | 2.8798 | 4000 | 0.7296          | 38.0634 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0