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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: bert-base-multilingual-cased
model-index:
  - name: comic-name-classification
    results: []

comic-name-classification

This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0445
  • Accuracy: 0.9937

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: 0.000125
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 25 0.0311 0.9933
No log 2.0 50 0.0330 0.9937
No log 3.0 75 0.0330 0.9933
No log 4.0 100 0.0350 0.9941
No log 5.0 125 0.0358 0.9937
No log 6.0 150 0.0363 0.9937
No log 7.0 175 0.0379 0.9945
No log 8.0 200 0.0356 0.9941
No log 9.0 225 0.0352 0.9941
No log 10.0 250 0.0376 0.9941
No log 11.0 275 0.0374 0.9941
No log 12.0 300 0.0387 0.9937
No log 13.0 325 0.0384 0.9941
No log 14.0 350 0.0392 0.9941
No log 15.0 375 0.0392 0.9941
No log 16.0 400 0.0394 0.9941
No log 17.0 425 0.0412 0.9945
No log 18.0 450 0.0404 0.9941
No log 19.0 475 0.0410 0.9941
0.0039 20.0 500 0.0414 0.9941
0.0039 21.0 525 0.0425 0.9941
0.0039 22.0 550 0.0416 0.9941
0.0039 23.0 575 0.0431 0.9941
0.0039 24.0 600 0.0439 0.9941
0.0039 25.0 625 0.0443 0.9941
0.0039 26.0 650 0.0440 0.9937
0.0039 27.0 675 0.0435 0.9937
0.0039 28.0 700 0.0428 0.9941
0.0039 29.0 725 0.0424 0.9941
0.0039 30.0 750 0.0431 0.9941
0.0039 31.0 775 0.0438 0.9941
0.0039 32.0 800 0.0419 0.9941
0.0039 33.0 825 0.0419 0.9941
0.0039 34.0 850 0.0416 0.9941
0.0039 35.0 875 0.0419 0.9941
0.0039 36.0 900 0.0430 0.9945
0.0039 37.0 925 0.0431 0.9941
0.0039 38.0 950 0.0439 0.9941
0.0039 39.0 975 0.0445 0.9937
0.0021 40.0 1000 0.0449 0.9937
0.0021 41.0 1025 0.0456 0.9941
0.0021 42.0 1050 0.0459 0.9941
0.0021 43.0 1075 0.0446 0.9937
0.0021 44.0 1100 0.0439 0.9941
0.0021 45.0 1125 0.0439 0.9941
0.0021 46.0 1150 0.0441 0.9941
0.0021 47.0 1175 0.0443 0.9941
0.0021 48.0 1200 0.0443 0.9937
0.0021 49.0 1225 0.0444 0.9937
0.0021 50.0 1250 0.0445 0.9937

Framework versions

  • PEFT 0.7.1
  • Transformers 4.37.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0