---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-ml
  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-tiny-ml

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2092
- Wer: 79.8896

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.4609        | 1.0316  | 500  | 1.1205          | 132.1684 |
| 0.9694        | 2.0632  | 1000 | 0.7589          | 100.8175 |
| 0.4373        | 4.0264  | 1500 | 0.2443          | 90.7214  |
| 0.2336        | 5.058   | 2000 | 0.2078          | 84.0997  |
| 0.1689        | 7.0212  | 2500 | 0.1942          | 79.9714  |
| 0.1322        | 8.0528  | 3000 | 0.1992          | 79.7466  |
| 0.1063        | 10.016  | 3500 | 0.2044          | 80.4210  |
| 0.0892        | 11.0476 | 4000 | 0.2040          | 78.7247  |
| 0.0755        | 13.0108 | 4500 | 0.2106          | 79.9918  |
| 0.0672        | 14.0424 | 5000 | 0.2092          | 79.8896  |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1