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---
license: mit
base_model: indolem/indobert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: IndoBERT_top5_bm25_rr5_10_epoch
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# IndoBERT_top5_bm25_rr5_10_epoch
This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0484
- Accuracy: 0.8476
- F1: 0.7027
- Precision: 0.7143
- Recall: 0.6915
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 0.2857 | 16 | 0.5745 | 0.7396 | 0.0 | 0.0 | 0.0 |
| No log | 0.5714 | 32 | 0.5547 | 0.7396 | 0.0 | 0.0 | 0.0 |
| No log | 0.8571 | 48 | 0.5288 | 0.7396 | 0.0 | 0.0 | 0.0 |
| No log | 1.1429 | 64 | 0.4822 | 0.8006 | 0.4462 | 0.8056 | 0.3085 |
| No log | 1.4286 | 80 | 0.4105 | 0.8310 | 0.6013 | 0.7797 | 0.4894 |
| No log | 1.7143 | 96 | 0.3975 | 0.8172 | 0.6633 | 0.6373 | 0.6915 |
| No log | 2.0 | 112 | 0.3980 | 0.8172 | 0.5541 | 0.7593 | 0.4362 |
| No log | 2.2857 | 128 | 0.4243 | 0.8144 | 0.6794 | 0.6174 | 0.7553 |
| No log | 2.5714 | 144 | 0.4404 | 0.8033 | 0.4580 | 0.8108 | 0.3191 |
| No log | 2.8571 | 160 | 0.3763 | 0.8504 | 0.6824 | 0.7632 | 0.6170 |
| No log | 3.1429 | 176 | 0.6084 | 0.7701 | 0.6527 | 0.5379 | 0.8298 |
| No log | 3.4286 | 192 | 0.4822 | 0.8587 | 0.7052 | 0.7722 | 0.6489 |
| No log | 3.7143 | 208 | 0.4620 | 0.8449 | 0.6164 | 0.8654 | 0.4787 |
| No log | 4.0 | 224 | 0.6729 | 0.7922 | 0.6809 | 0.5674 | 0.8511 |
| No log | 4.2857 | 240 | 0.7337 | 0.8449 | 0.7143 | 0.6863 | 0.7447 |
| No log | 4.5714 | 256 | 1.0946 | 0.7812 | 0.6580 | 0.5547 | 0.8085 |
| No log | 4.8571 | 272 | 1.0382 | 0.7535 | 0.6397 | 0.5163 | 0.8404 |
| No log | 5.1429 | 288 | 0.5228 | 0.8532 | 0.6971 | 0.7531 | 0.6489 |
| No log | 5.4286 | 304 | 0.8456 | 0.8255 | 0.6897 | 0.6422 | 0.7447 |
| No log | 5.7143 | 320 | 0.8758 | 0.8504 | 0.6860 | 0.7564 | 0.6277 |
| No log | 6.0 | 336 | 0.9307 | 0.8116 | 0.6699 | 0.6161 | 0.7340 |
| No log | 6.2857 | 352 | 0.7016 | 0.8421 | 0.6743 | 0.7284 | 0.6277 |
| No log | 6.5714 | 368 | 0.6991 | 0.8560 | 0.6941 | 0.7763 | 0.6277 |
| No log | 6.8571 | 384 | 0.7400 | 0.8504 | 0.7188 | 0.7041 | 0.7340 |
| No log | 7.1429 | 400 | 0.8463 | 0.8532 | 0.7166 | 0.7204 | 0.7128 |
| No log | 7.4286 | 416 | 0.8996 | 0.8560 | 0.7234 | 0.7234 | 0.7234 |
| No log | 7.7143 | 432 | 0.9267 | 0.8504 | 0.7158 | 0.7083 | 0.7234 |
| No log | 8.0 | 448 | 0.9227 | 0.8587 | 0.7182 | 0.7471 | 0.6915 |
| No log | 8.2857 | 464 | 0.9840 | 0.8476 | 0.7027 | 0.7143 | 0.6915 |
| No log | 8.5714 | 480 | 1.0115 | 0.8449 | 0.6923 | 0.7159 | 0.6702 |
| No log | 8.8571 | 496 | 1.0437 | 0.8449 | 0.6957 | 0.7111 | 0.6809 |
| 0.2421 | 9.1429 | 512 | 1.0514 | 0.8449 | 0.6957 | 0.7111 | 0.6809 |
| 0.2421 | 9.4286 | 528 | 1.0470 | 0.8476 | 0.7027 | 0.7143 | 0.6915 |
| 0.2421 | 9.7143 | 544 | 1.0438 | 0.8476 | 0.7027 | 0.7143 | 0.6915 |
| 0.2421 | 10.0 | 560 | 1.0484 | 0.8476 | 0.7027 | 0.7143 | 0.6915 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Tokenizers 0.19.1
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