qa_kor_math_2 / README.md
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metadata
license: mit
base_model: hyunwoongko/kobart
tags:
  - generated_from_trainer
model-index:
  - name: qa_kor_math_2
    results: []

qa_kor_math_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: 0.1234

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: 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: 20

Training results

Training Loss Epoch Step Validation Loss
No log 0.56 100 3.2887
No log 1.13 200 0.8359
No log 1.69 300 0.4944
No log 2.26 400 0.3843
2.4704 2.82 500 0.3349
2.4704 3.39 600 0.3005
2.4704 3.95 700 0.2768
2.4704 4.52 800 0.2641
2.4704 5.08 900 0.2479
0.3213 5.65 1000 0.2335
0.3213 6.21 1100 0.2208
0.3213 6.78 1200 0.2117
0.3213 7.34 1300 0.2041
0.3213 7.91 1400 0.1964
0.2503 8.47 1500 0.1876
0.2503 9.04 1600 0.1790
0.2503 9.6 1700 0.1745
0.2503 10.17 1800 0.1673
0.2503 10.73 1900 0.1623
0.2141 11.3 2000 0.1579
0.2141 11.86 2100 0.1527
0.2141 12.43 2200 0.1494
0.2141 12.99 2300 0.1438
0.2141 13.56 2400 0.1427
0.1873 14.12 2500 0.1386
0.1873 14.69 2600 0.1347
0.1873 15.25 2700 0.1334
0.1873 15.82 2800 0.1321
0.1873 16.38 2900 0.1295
0.1718 16.95 3000 0.1276
0.1718 17.51 3100 0.1263
0.1718 18.08 3200 0.1255
0.1718 18.64 3300 0.1244
0.1718 19.21 3400 0.1240
0.1628 19.77 3500 0.1234

Framework versions

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