---
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny En - SF test
  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 En - SF test

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the SF 200 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7031
- Wer: 62.9291

## 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: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.5292        | 8.8889  | 100  | 1.0957          | 59.9542 |
| 0.0462        | 17.7778 | 200  | 1.2314          | 57.6659 |
| 0.0058        | 26.6667 | 300  | 1.4473          | 63.6156 |
| 0.0029        | 35.5556 | 400  | 1.5361          | 63.6156 |
| 0.0017        | 44.4444 | 500  | 1.6016          | 60.6407 |
| 0.0012        | 53.3333 | 600  | 1.6367          | 62.9291 |
| 0.0009        | 62.2222 | 700  | 1.6670          | 63.6156 |
| 0.0008        | 71.1111 | 800  | 1.6875          | 63.6156 |
| 0.0007        | 80.0    | 900  | 1.6992          | 63.6156 |
| 0.0007        | 88.8889 | 1000 | 1.7031          | 62.9291 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1