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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 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: 0.2092
- Cer: 12.0743
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.186 | 0.9980 | 488 | 1.2024 | 49.3007 |
| 0.3895 | 1.9959 | 976 | 0.4851 | 26.5471 |
| 0.2054 | 2.9939 | 1464 | 0.3152 | 17.7208 |
| 0.1232 | 3.9918 | 1952 | 0.2593 | 16.5314 |
| 0.0844 | 4.9898 | 2440 | 0.2355 | 14.3364 |
| 0.0557 | 5.9877 | 2928 | 0.2269 | 15.5339 |
| 0.0367 | 6.9857 | 3416 | 0.2197 | 13.5042 |
| 0.0265 | 7.9836 | 3904 | 0.2149 | 13.1851 |
| 0.0199 | 8.9816 | 4392 | 0.2107 | 13.2591 |
| 0.0131 | 9.9796 | 4880 | 0.2113 | 14.0000 |
| 0.0084 | 10.9775 | 5368 | 0.2118 | 14.3977 |
| 0.006 | 11.9755 | 5856 | 0.2103 | 14.0104 |
| 0.0046 | 12.9734 | 6344 | 0.2109 | 13.5192 |
| 0.0036 | 13.9714 | 6832 | 0.2086 | 13.4972 |
| 0.003 | 14.9693 | 7320 | 0.2074 | 13.3643 |
| 0.0027 | 15.9673 | 7808 | 0.2083 | 13.7666 |
| 0.0023 | 16.9652 | 8296 | 0.2095 | 12.4280 |
| 0.0021 | 17.9632 | 8784 | 0.2105 | 12.3968 |
| 0.0019 | 18.9611 | 9272 | 0.2095 | 12.4581 |
| 0.0018 | 19.9591 | 9760 | 0.2092 | 12.0743 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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