---
library_name: transformers
language:
- zh
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper_largev3_motor_zh
  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_largev3_motor_zh

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1474
- Wer: 687.0393

## 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: 4
- 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: 100
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer       |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 0.1996        | 0.0905 | 300  | 0.2141          | 335.3766  |
| 0.2683        | 0.1809 | 600  | 0.2006          | 354.0665  |
| 0.178         | 0.2714 | 900  | 0.1823          | 371.9752  |
| 0.0837        | 0.3619 | 1200 | 0.1587          | 1194.9519 |
| 0.0985        | 0.4524 | 1500 | 0.1474          | 687.0393  |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3