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-E10_Yfreq-SA
results: []
whisper-small-ko-E10_Yfreq-SA
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: 0.2060
- Cer: 5.8917
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 |
---|---|---|---|---|
0.3564 | 0.13 | 100 | 0.2919 | 7.1898 |
0.2354 | 0.26 | 200 | 0.2478 | 6.7023 |
0.21 | 0.39 | 300 | 0.2349 | 7.3191 |
0.1999 | 0.52 | 400 | 0.2270 | 7.0665 |
0.1883 | 0.64 | 500 | 0.2227 | 6.8961 |
0.1844 | 0.77 | 600 | 0.2195 | 6.4027 |
0.1631 | 0.9 | 700 | 0.2156 | 6.1560 |
0.0977 | 1.03 | 800 | 0.2142 | 6.0738 |
0.087 | 1.16 | 900 | 0.2144 | 6.0385 |
0.0985 | 1.29 | 1000 | 0.2119 | 6.0033 |
0.0763 | 1.42 | 1100 | 0.2110 | 5.9034 |
0.0906 | 1.55 | 1200 | 0.2088 | 5.8741 |
0.0922 | 1.68 | 1300 | 0.2066 | 5.8564 |
0.079 | 1.81 | 1400 | 0.2060 | 5.8623 |
0.0771 | 1.93 | 1500 | 0.2060 | 5.8917 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0