---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large Five 5K None - 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 Large Five 5K None - Chee Li

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Google Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1774
- Wer: 10.1251

## 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: 600
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0557        | 1.0560 | 1000 | 0.1488          | 11.4913 |
| 0.0171        | 2.1119 | 2000 | 0.1522          | 9.5367  |
| 0.0085        | 3.1679 | 3000 | 0.1630          | 8.6409  |
| 0.0015        | 4.2239 | 4000 | 0.1705          | 10.7759 |
| 0.0007        | 5.2798 | 5000 | 0.1774          | 10.1251 |


### Framework versions

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