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---
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-extreme-lr-5e-05-batchsize-4-encmaxlen-512-decmaxlen-256-abs
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. -->
# bert2bert-extreme-lr-5e-05-batchsize-4-encmaxlen-512-decmaxlen-256-abs
This model was trained from scratch on the id_liputan6 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8067
- R1 Precision: 0.3498
- R1 Recall: 0.2552
- R1 Fmeasure: 0.2924
- R2 Precision: 0.1424
- R2 Recall: 0.1011
- R2 Fmeasure: 0.1171
- Rl Precision: 0.2867
- Rl Recall: 0.2094
- Rl Fmeasure: 0.2398
## 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: 18
- eval_batch_size: 18
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | R1 Precision | R1 Recall | R1 Fmeasure | R2 Precision | R2 Recall | R2 Fmeasure | Rl Precision | Rl Recall | Rl Fmeasure |
|:-------------:|:-----:|:------:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
| 2.3503 | 1.0 | 10772 | 2.6541 | 0.3481 | 0.2534 | 0.2906 | 0.1416 | 0.1004 | 0.1163 | 0.2906 | 0.2118 | 0.2427 |
| 1.5052 | 2.0 | 21544 | 2.5634 | 0.3506 | 0.2547 | 0.2924 | 0.1434 | 0.1018 | 0.1179 | 0.2914 | 0.2121 | 0.2432 |
| 1.3217 | 3.0 | 32316 | 2.5531 | 0.358 | 0.2605 | 0.2988 | 0.1477 | 0.1048 | 0.1214 | 0.2974 | 0.2168 | 0.2485 |
| 1.193 | 4.0 | 43088 | 2.5764 | 0.3619 | 0.2648 | 0.3029 | 0.1506 | 0.1074 | 0.1241 | 0.2996 | 0.2192 | 0.2508 |
| 1.0839 | 5.0 | 53860 | 2.6102 | 0.3556 | 0.2596 | 0.2973 | 0.1468 | 0.1044 | 0.1207 | 0.294 | 0.2149 | 0.246 |
| 0.9875 | 6.0 | 64632 | 2.6594 | 0.3569 | 0.2617 | 0.2992 | 0.1467 | 0.1048 | 0.1211 | 0.2942 | 0.2159 | 0.2467 |
| 0.8956 | 7.0 | 75404 | 2.7380 | 0.3565 | 0.2607 | 0.2983 | 0.1469 | 0.1048 | 0.1211 | 0.2951 | 0.2161 | 0.2471 |
| 0.8147 | 8.0 | 86176 | 2.8133 | 0.3584 | 0.2625 | 0.3002 | 0.1475 | 0.1053 | 0.1217 | 0.2955 | 0.2166 | 0.2476 |
| 0.7345 | 9.0 | 96948 | 2.9544 | 0.3577 | 0.2602 | 0.2985 | 0.1476 | 0.1046 | 0.1212 | 0.2933 | 0.2134 | 0.2448 |
| 0.6626 | 10.0 | 107720 | 3.0282 | 0.3565 | 0.2602 | 0.2981 | 0.145 | 0.1034 | 0.1195 | 0.2926 | 0.2138 | 0.2448 |
| 0.5974 | 11.0 | 118492 | 3.1423 | 0.3547 | 0.2592 | 0.2967 | 0.1448 | 0.1032 | 0.1193 | 0.2901 | 0.2122 | 0.2428 |
| 0.5357 | 12.0 | 129264 | 3.2344 | 0.3533 | 0.2579 | 0.2954 | 0.1446 | 0.1029 | 0.119 | 0.2892 | 0.2113 | 0.242 |
| 0.4262 | 13.0 | 140036 | 3.3609 | 0.3523 | 0.2571 | 0.2946 | 0.1429 | 0.1018 | 0.1177 | 0.2888 | 0.211 | 0.2416 |
| 0.3724 | 14.0 | 150808 | 3.4457 | 0.3558 | 0.2603 | 0.2979 | 0.1459 | 0.1041 | 0.1203 | 0.2913 | 0.2133 | 0.2439 |
| 0.3318 | 15.0 | 161580 | 3.5539 | 0.3522 | 0.2571 | 0.2945 | 0.144 | 0.1024 | 0.1185 | 0.2888 | 0.2109 | 0.2415 |
| 0.297 | 16.0 | 172352 | 3.6266 | 0.3531 | 0.2573 | 0.2949 | 0.1441 | 0.1021 | 0.1183 | 0.2892 | 0.2108 | 0.2415 |
| 0.2648 | 17.0 | 183124 | 3.6790 | 0.353 | 0.258 | 0.2954 | 0.1431 | 0.102 | 0.1179 | 0.289 | 0.2114 | 0.2419 |
| 0.2378 | 18.0 | 193896 | 3.7428 | 0.3504 | 0.2557 | 0.2929 | 0.1425 | 0.1013 | 0.1172 | 0.2869 | 0.2096 | 0.24 |
| 0.2155 | 19.0 | 204668 | 3.7795 | 0.352 | 0.2572 | 0.2945 | 0.1435 | 0.1021 | 0.1181 | 0.2891 | 0.2113 | 0.2419 |
| 0.1976 | 20.0 | 215440 | 3.8067 | 0.3498 | 0.2552 | 0.2924 | 0.1424 | 0.1011 | 0.1171 | 0.2867 | 0.2094 | 0.2398 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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