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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3942 | 1.0 | 122 | 0.3128 | 0.8797 | 0.8858 | 0.8174 | 0.8419 |
| 0.2168 | 2.0 | 244 | 0.3044 | 0.8897 | 0.8659 | 0.8695 | 0.8676 |
| 0.1372 | 3.0 | 366 | 0.5318 | 0.8897 | 0.8852 | 0.8420 | 0.8595 |
| 0.0957 | 4.0 | 488 | 0.4765 | 0.8947 | 0.8676 | 0.8880 | 0.8766 |
| 0.0674 | 5.0 | 610 | 0.5523 | 0.8872 | 0.8577 | 0.9027 | 0.8729 |
| 0.0535 | 6.0 | 732 | 0.5159 | 0.9073 | 0.8888 | 0.8869 | 0.8879 |
| 0.027 | 7.0 | 854 | 0.5941 | 0.8872 | 0.8634 | 0.8652 | 0.8643 |
| 0.0223 | 8.0 | 976 | 0.7166 | 0.8797 | 0.8549 | 0.8549 | 0.8549 |
| 0.0145 | 9.0 | 1098 | 0.7023 | 0.9023 | 0.8802 | 0.8858 | 0.8830 |
| 0.0106 | 10.0 | 1220 | 0.6993 | 0.9048 | 0.8881 | 0.8801 | 0.8839 |
| 0.0093 | 11.0 | 1342 | 0.8274 | 0.8947 | 0.8789 | 0.8630 | 0.8704 |
| 0.0086 | 12.0 | 1464 | 0.7972 | 0.8972 | 0.8796 | 0.8698 | 0.8745 |
| 0.0106 | 13.0 | 1586 | 0.7592 | 0.8972 | 0.8715 | 0.8873 | 0.8787 |
| 0.0072 | 14.0 | 1708 | 0.7834 | 0.8997 | 0.8748 | 0.8891 | 0.8814 |
| 0.0098 | 15.0 | 1830 | 0.8049 | 0.8997 | 0.8767 | 0.8841 | 0.8803 |
| 0.0058 | 16.0 | 1952 | 0.7671 | 0.8997 | 0.8767 | 0.8841 | 0.8803 |
| 0.0035 | 17.0 | 2074 | 0.8085 | 0.9023 | 0.8758 | 0.8983 | 0.8857 |
| 0.0052 | 18.0 | 2196 | 0.7721 | 0.8997 | 0.8757 | 0.8866 | 0.8808 |
| 0.0028 | 19.0 | 2318 | 0.8359 | 0.8972 | 0.8708 | 0.8898 | 0.8793 |
| 0.0033 | 20.0 | 2440 | 0.8336 | 0.8972 | 0.8708 | 0.8898 | 0.8793 |
indolem/indobert-base-uncasedmodel.safetensors 447 MBdefault/pytorch_model_head.bin 101 MBsentiment/pytorch_model_head.bin 2 MBsentiment-lora/pytorch_adapter.bin 607.7 kBtraining_args.bin 5 kB