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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: 0.2344
- Cer: 12.5425
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.1066 | 0.9980 | 488 | 1.2078 | 49.8428 |
| 0.3421 | 1.9959 | 976 | 0.5032 | 26.3703 |
| 0.1775 | 2.9939 | 1464 | 0.3401 | 17.7012 |
| 0.1069 | 3.9918 | 1952 | 0.2920 | 18.6536 |
| 0.0719 | 4.9898 | 2440 | 0.2630 | 15.3975 |
| 0.0467 | 5.9877 | 2928 | 0.2507 | 15.8182 |
| 0.0302 | 6.9857 | 3416 | 0.2454 | 16.1523 |
| 0.0217 | 7.9836 | 3904 | 0.2407 | 14.2000 |
| 0.0157 | 8.9816 | 4392 | 0.2387 | 13.9053 |
| 0.0105 | 9.9796 | 4880 | 0.2373 | 14.6473 |
| 0.0066 | 10.9775 | 5368 | 0.2338 | 15.3628 |
| 0.005 | 11.9755 | 5856 | 0.2352 | 14.5040 |
| 0.0038 | 12.9734 | 6344 | 0.2321 | 14.1411 |
| 0.0035 | 13.9714 | 6832 | 0.2348 | 12.9644 |
| 0.0025 | 14.9693 | 7320 | 0.2335 | 13.4348 |
| 0.0022 | 15.9673 | 7808 | 0.2337 | 13.8186 |
| 0.0019 | 16.9652 | 8296 | 0.2345 | 13.7897 |
| 0.0018 | 17.9632 | 8784 | 0.2347 | 12.8430 |
| 0.0016 | 18.9611 | 9272 | 0.2341 | 13.1724 |
| 0.0016 | 19.9591 | 9760 | 0.2344 | 12.5425 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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