Edit model card

sentiment-base-2

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

  • Loss: 0.8886
  • Accuracy: 0.8922
  • Precision: 0.8719
  • Recall: 0.8662
  • F1: 0.8690

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: 5e-05
  • train_batch_size: 30
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20.0

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.3808 1.0 122 0.3794 0.8647 0.8737 0.7917 0.8186
0.221 2.0 244 0.2851 0.8722 0.8562 0.8271 0.8395
0.1363 3.0 366 0.3832 0.8947 0.8757 0.8680 0.8717
0.099 4.0 488 0.4968 0.8972 0.8869 0.8598 0.8717
0.0702 5.0 610 0.5205 0.8697 0.8503 0.8278 0.8377
0.0469 6.0 732 0.5740 0.8747 0.8552 0.8363 0.8448
0.0328 7.0 854 0.6012 0.8847 0.8581 0.8684 0.8629
0.0284 8.0 976 0.5403 0.8972 0.8812 0.8673 0.8738
0.019 9.0 1098 0.5909 0.8922 0.8657 0.8813 0.8728
0.016 10.0 1220 0.8931 0.8822 0.8694 0.8392 0.8521
0.0167 11.0 1342 0.6618 0.8972 0.8781 0.8723 0.8751
0.0168 12.0 1464 0.7513 0.9023 0.8842 0.8783 0.8812
0.0064 13.0 1586 0.7513 0.8997 0.8819 0.8741 0.8778
0.0078 14.0 1708 0.8152 0.8947 0.8789 0.8630 0.8704
0.0064 15.0 1830 0.7460 0.8997 0.8778 0.8816 0.8797
0.0055 16.0 1952 0.8232 0.8922 0.8734 0.8637 0.8683
0.006 17.0 2074 0.8421 0.8947 0.8757 0.8680 0.8717
0.0052 18.0 2196 0.8442 0.8872 0.8624 0.8677 0.8650
0.0035 19.0 2318 0.8841 0.8897 0.8682 0.8645 0.8663
0.0013 20.0 2440 0.8886 0.8922 0.8719 0.8662 0.8690

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.15.2
Downloads last month
2
Safetensors
Model size
112M params
Tensor type
F32
·
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for apwic/sentiment-base-2

Finetuned
this model