---
language:
- zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- formospeech/hat_asr_aligned
model-index:
- name: Whisper Tiny Hakka Condenser
  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 Hakka Condenser

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the HAT ASR Aligned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2216
- Cer: 13.1863

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 976
- training_steps: 9760
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.2175        | 0.9980  | 488  | 1.2419          | 50.2601 |
| 0.3915        | 1.9959  | 976  | 0.5156          | 27.2673 |
| 0.1993        | 2.9939  | 1464 | 0.3351          | 18.1346 |
| 0.121         | 3.9918  | 1952 | 0.2783          | 16.5268 |
| 0.0808        | 4.9898  | 2440 | 0.2555          | 15.1964 |
| 0.0538        | 5.9877  | 2928 | 0.2460          | 14.7722 |
| 0.0348        | 6.9857  | 3416 | 0.2305          | 14.2647 |
| 0.0255        | 7.9836  | 3904 | 0.2224          | 13.6105 |
| 0.019         | 8.9816  | 4392 | 0.2232          | 14.8635 |
| 0.0126        | 9.9796  | 4880 | 0.2214          | 13.4857 |
| 0.0079        | 10.9775 | 5368 | 0.2234          | 13.6510 |
| 0.0058        | 11.9755 | 5856 | 0.2211          | 13.5261 |
| 0.0045        | 12.9734 | 6344 | 0.2206          | 13.9920 |
| 0.0034        | 13.9714 | 6832 | 0.2210          | 13.8082 |
| 0.0029        | 14.9693 | 7320 | 0.2235          | 12.1090 |
| 0.0025        | 15.9673 | 7808 | 0.2203          | 12.2974 |
| 0.0022        | 16.9652 | 8296 | 0.2217          | 12.2847 |
| 0.002         | 17.9632 | 8784 | 0.2218          | 13.2291 |
| 0.0018        | 18.9611 | 9272 | 0.2216          | 13.3285 |
| 0.0018        | 19.9591 | 9760 | 0.2216          | 13.1863 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1