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---
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 Simulated Webcam
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 Simulated Webcam
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: 0.1884
- Cer: 9.2679
## 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: 0.0001
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2208 | 0.9980 | 488 | 0.3739 | 25.8594 |
| 0.1188 | 1.9959 | 976 | 0.2960 | 24.9116 |
| 0.0782 | 2.9939 | 1464 | 0.2618 | 18.5519 |
| 0.041 | 3.9918 | 1952 | 0.2452 | 18.9357 |
| 0.0251 | 4.9898 | 2440 | 0.2292 | 17.5810 |
| 0.0169 | 5.9877 | 2928 | 0.2557 | 15.4137 |
| 0.011 | 6.9857 | 3416 | 0.2254 | 17.0585 |
| 0.0072 | 7.9836 | 3904 | 0.2343 | 12.5136 |
| 0.0051 | 8.9816 | 4392 | 0.2362 | 12.3864 |
| 0.0044 | 9.9796 | 4880 | 0.2261 | 12.0570 |
| 0.0024 | 10.9775 | 5368 | 0.2191 | 11.3219 |
| 0.0024 | 11.9755 | 5856 | 0.2158 | 12.1056 |
| 0.0012 | 12.9734 | 6344 | 0.2027 | 9.9140 |
| 0.0008 | 13.9714 | 6832 | 0.2002 | 9.7973 |
| 0.0003 | 14.9693 | 7320 | 0.2084 | 10.1822 |
| 0.001 | 15.9673 | 7808 | 0.1990 | 9.9082 |
| 0.0002 | 16.9652 | 8296 | 0.1946 | 9.4355 |
| 0.0001 | 17.9632 | 8784 | 0.1909 | 9.1361 |
| 0.0001 | 18.9611 | 9272 | 0.1901 | 9.0517 |
| 0.0001 | 19.9591 | 9760 | 0.1884 | 9.2679 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|