qa_kor_hospital_2 / README.md
idah4's picture
Model save
eb03bb9 verified
metadata
license: mit
base_model: hyunwoongko/kobart
tags:
  - generated_from_trainer
model-index:
  - name: qa_kor_hospital_2
    results: []

qa_kor_hospital_2

This model is a fine-tuned version of hyunwoongko/kobart on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1627

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 400
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
No log 0.11 100 1.7331
No log 0.21 200 1.4674
No log 0.32 300 1.3987
No log 0.42 400 1.3671
2.0632 0.53 500 1.4153
2.0632 0.63 600 1.3083
2.0632 0.74 700 1.2721
2.0632 0.85 800 1.2572
2.0632 0.95 900 1.2314
1.3262 1.06 1000 1.2468
1.3262 1.16 1100 1.2230
1.3262 1.27 1200 1.2158
1.3262 1.37 1300 1.2019
1.3262 1.48 1400 1.2011
1.1014 1.59 1500 1.1909
1.1014 1.69 1600 1.1768
1.1014 1.8 1700 1.1648
1.1014 1.9 1800 1.1608
1.1014 2.01 1900 1.1736
1.0434 2.11 2000 1.1865
1.0434 2.22 2100 1.1853
1.0434 2.33 2200 1.1890
1.0434 2.43 2300 1.1765
1.0434 2.54 2400 1.1696
0.8701 2.64 2500 1.1720
0.8701 2.75 2600 1.1611
0.8701 2.85 2700 1.1641
0.8701 2.96 2800 1.1627

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2