metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_elder
model-index:
- name: whisper-small-ko-E50_Yfreq
results: []
whisper-small-ko-E50_Yfreq
This model is a fine-tuned version of openai/whisper-small on the aihub elder over 70 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1713
- Cer: 5.1046
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.3825 | 0.13 | 100 | 0.2698 | 6.7787 |
| 0.2401 | 0.26 | 200 | 0.2154 | 5.9269 |
| 0.227 | 0.39 | 300 | 0.2012 | 5.8212 |
| 0.1937 | 0.52 | 400 | 0.1922 | 5.4511 |
| 0.2127 | 0.64 | 500 | 0.1885 | 5.3454 |
| 0.1987 | 0.77 | 600 | 0.1835 | 5.3395 |
| 0.1823 | 0.9 | 700 | 0.1833 | 5.2925 |
| 0.0906 | 1.03 | 800 | 0.1783 | 5.1398 |
| 0.0841 | 1.16 | 900 | 0.1787 | 4.9930 |
| 0.0945 | 1.29 | 1000 | 0.1786 | 6.1090 |
| 0.0898 | 1.42 | 1100 | 0.1799 | 5.3630 |
| 0.0843 | 1.55 | 1200 | 0.1746 | 5.3983 |
| 0.0989 | 1.68 | 1300 | 0.1711 | 5.1163 |
| 0.0744 | 1.81 | 1400 | 0.1718 | 5.1339 |
| 0.0796 | 1.93 | 1500 | 0.1713 | 5.1046 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0