---
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Five - Chee Li
  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 Five - Chee Li

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4348
- Wer: 21.6569

## 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: 850
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3047        | 1.0560 | 1000 | 0.4050          | 22.7955 |
| 0.1771        | 2.1119 | 2000 | 0.3811          | 21.0509 |
| 0.1176        | 3.1679 | 3000 | 0.3864          | 21.3429 |
| 0.0852        | 4.2239 | 4000 | 0.3962          | 20.7720 |
| 0.0443        | 5.2798 | 5000 | 0.4100          | 21.4523 |
| 0.0265        | 6.3358 | 6000 | 0.4234          | 21.3823 |
| 0.0254        | 7.3918 | 7000 | 0.4310          | 21.7783 |
| 0.0188        | 8.4477 | 8000 | 0.4348          | 21.6569 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1