---
library_name: transformers
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper small TW - from gy
  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 TW - from gy

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0166
- Wer: 16.8640

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0046        | 3.4965  | 1000 | 0.0193          | 19.7097 |
| 0.0007        | 6.9930  | 2000 | 0.0161          | 17.3797 |
| 0.0001        | 10.4895 | 3000 | 0.0163          | 16.7876 |
| 0.0001        | 13.9860 | 4000 | 0.0165          | 16.8640 |
| 0.0001        | 17.4825 | 5000 | 0.0166          | 16.8640 |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.21.4