aspect_model / README.md
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metadata
license: mit
base_model: indobenchmark/indobert-base-p2
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: aspect_model
    results: []

aspect_model

This model is a fine-tuned version of indobenchmark/indobert-base-p2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3490
  • Accuracy: 0.8084

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: 2e-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
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 72 0.6516 0.7735
No log 2.0 144 0.6119 0.7909
No log 3.0 216 0.6152 0.8049
No log 4.0 288 0.7480 0.8118
No log 5.0 360 1.0121 0.7770
No log 6.0 432 1.0780 0.7909
0.27 7.0 504 1.1602 0.7840
0.27 8.0 576 1.2136 0.8014
0.27 9.0 648 1.2490 0.8014
0.27 10.0 720 1.3102 0.7840
0.27 11.0 792 1.3184 0.8049
0.27 12.0 864 1.3255 0.8014
0.27 13.0 936 1.3192 0.8049
0.0022 14.0 1008 1.3229 0.7944
0.0022 15.0 1080 1.3415 0.8014
0.0022 16.0 1152 1.3515 0.7909
0.0022 17.0 1224 1.3544 0.7944
0.0022 18.0 1296 1.3529 0.7944
0.0022 19.0 1368 1.3484 0.8084
0.0022 20.0 1440 1.3490 0.8084

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0