metadata
library_name: transformers
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- formospeech/hat_asr_aligned
model-index:
- name: Whisper Small Hakka Condenser
results: []
Whisper Small Hakka Condenser
This model is a fine-tuned version of openai/whisper-small on the HAT ASR Aligned dataset. It achieves the following results on the evaluation set:
- Loss: 0.1313
- Cer: 6.1701
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use 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: 1366
- training_steps: 13664
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0405 | 3.9933 | 1952 | 0.1910 | 14.4081 |
| 0.0121 | 7.9852 | 3904 | 0.1850 | 9.9556 |
| 0.0061 | 11.9770 | 5856 | 0.1636 | 8.6610 |
| 0.0032 | 15.9688 | 7808 | 0.1563 | 7.6207 |
| 0.0004 | 19.9606 | 9760 | 0.1421 | 6.5978 |
| 0.0001 | 23.9524 | 11712 | 0.1332 | 6.4117 |
| 0.0 | 27.9442 | 13664 | 0.1313 | 6.1701 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.0.0.post304
- Datasets 3.3.2
- Tokenizers 0.21.0