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metadata
license: apache-2.0
base_model: line-corporation/line-distilbert-base-japanese
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: factual-consistency-classification-ja
    results: []

factual-consistency-classification-ja

This model is a fine-tuned version of line-corporation/line-distilbert-base-japanese on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8034
  • Accuracy: 0.6230

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: 64
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: tpu
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 306 1.0539 0.2891
1.0502 2.0 612 1.0074 0.3203
1.0502 3.0 918 0.9738 0.3711
0.9895 4.0 1224 0.9452 0.4453
0.9483 5.0 1530 0.9245 0.4766
0.9483 6.0 1836 0.9041 0.5566
0.918 7.0 2142 0.8945 0.5117
0.918 8.0 2448 0.8853 0.5
0.9002 9.0 2754 0.8786 0.4922
0.884 10.0 3060 0.8658 0.5352
0.884 11.0 3366 0.8614 0.5176
0.8697 12.0 3672 0.8467 0.5938
0.8697 13.0 3978 0.8429 0.5801
0.8648 14.0 4284 0.8386 0.5703
0.8571 15.0 4590 0.8311 0.5996
0.8571 16.0 4896 0.8289 0.5879
0.8478 17.0 5202 0.8285 0.5762
0.8468 18.0 5508 0.8193 0.6152
0.8468 19.0 5814 0.8192 0.5957
0.8439 20.0 6120 0.8165 0.5996
0.8439 21.0 6426 0.8157 0.5918
0.8396 22.0 6732 0.8120 0.6055
0.8354 23.0 7038 0.8103 0.6055
0.8354 24.0 7344 0.8091 0.6035
0.8362 25.0 7650 0.8055 0.6152
0.8362 26.0 7956 0.8055 0.6074
0.8334 27.0 8262 0.8045 0.6211
0.8325 28.0 8568 0.8037 0.6191
0.8325 29.0 8874 0.8034 0.6230
0.833 30.0 9180 0.8034 0.6230

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.0+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.0