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bert2bert-model2

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Extreme train 20 epochs with 18 batch size

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  1. README.md +20 -20
  2. model.safetensors +1 -1
  3. runs/Apr16_07-18-52_728561d7d15f/events.out.tfevents.1713283565.728561d7d15f.381.1 +2 -2
README.md CHANGED
@@ -15,16 +15,16 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on the id_liputan6 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2026
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- - R1 Precision: 0.5676
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- - R1 Recall: 0.2496
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- - R1 Fmeasure: 0.3412
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- - R2 Precision: 0.4787
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- - R2 Recall: 0.1992
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- - R2 Fmeasure: 0.2767
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- - Rl Precision: 0.5419
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- - Rl Recall: 0.2376
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- - Rl Fmeasure: 0.3251
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  ## Model description
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@@ -56,16 +56,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | R1 Precision | R1 Recall | R1 Fmeasure | R2 Precision | R2 Recall | R2 Fmeasure | Rl Precision | Rl Recall | Rl Fmeasure |
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  |:-------------:|:-----:|:------:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
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- | 0.9444 | 1.0 | 10772 | 0.1834 | 0.5328 | 0.2367 | 0.3226 | 0.4379 | 0.1842 | 0.2551 | 0.5062 | 0.2243 | 0.3059 |
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- | 0.1703 | 2.0 | 21544 | 0.1605 | 0.565 | 0.2474 | 0.3386 | 0.4764 | 0.1974 | 0.2745 | 0.5403 | 0.236 | 0.3232 |
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- | 0.1407 | 3.0 | 32316 | 0.1567 | 0.5553 | 0.242 | 0.3318 | 0.4652 | 0.1914 | 0.2669 | 0.5302 | 0.2303 | 0.3161 |
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- | 0.1199 | 4.0 | 43088 | 0.1565 | 0.5651 | 0.2446 | 0.3361 | 0.4774 | 0.1954 | 0.2728 | 0.5408 | 0.2333 | 0.3209 |
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- | 0.1022 | 5.0 | 53860 | 0.1578 | 0.5681 | 0.2449 | 0.3368 | 0.4818 | 0.1962 | 0.2744 | 0.5442 | 0.2338 | 0.322 |
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- | 0.0864 | 6.0 | 64632 | 0.1614 | 0.5657 | 0.2457 | 0.3373 | 0.4779 | 0.196 | 0.2735 | 0.5409 | 0.2341 | 0.3217 |
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- | 0.0709 | 7.0 | 75404 | 0.1712 | 0.5669 | 0.2473 | 0.339 | 0.4782 | 0.1974 | 0.275 | 0.5418 | 0.2356 | 0.3233 |
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- | 0.0579 | 8.0 | 86176 | 0.1830 | 0.5629 | 0.2499 | 0.3407 | 0.472 | 0.1987 | 0.2749 | 0.5366 | 0.2377 | 0.3242 |
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- | 0.0458 | 9.0 | 96948 | 0.1955 | 0.5708 | 0.2513 | 0.3435 | 0.4817 | 0.2009 | 0.2789 | 0.5451 | 0.2393 | 0.3273 |
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- | 0.0364 | 10.0 | 107720 | 0.2026 | 0.5676 | 0.2496 | 0.3412 | 0.4787 | 0.1992 | 0.2767 | 0.5419 | 0.2376 | 0.3251 |
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  ### Framework versions
 
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  This model was trained from scratch on the id_liputan6 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0021
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+ - R1 Precision: 0.3553
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+ - R1 Recall: 0.2599
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+ - R1 Fmeasure: 0.2974
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+ - R2 Precision: 0.1458
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+ - R2 Recall: 0.1039
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+ - R2 Fmeasure: 0.12
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+ - Rl Precision: 0.2925
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+ - Rl Recall: 0.2139
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+ - Rl Fmeasure: 0.2448
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | R1 Precision | R1 Recall | R1 Fmeasure | R2 Precision | R2 Recall | R2 Fmeasure | Rl Precision | Rl Recall | Rl Fmeasure |
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  |:-------------:|:-----:|:------:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
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+ | 1.7393 | 1.0 | 10772 | 2.6782 | 0.3432 | 0.2497 | 0.2864 | 0.1375 | 0.0975 | 0.113 | 0.2828 | 0.206 | 0.2361 |
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+ | 1.4091 | 2.0 | 21544 | 2.6063 | 0.3486 | 0.2534 | 0.2907 | 0.142 | 0.1004 | 0.1164 | 0.2878 | 0.2094 | 0.2401 |
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+ | 1.246 | 3.0 | 32316 | 2.6079 | 0.3535 | 0.2578 | 0.2955 | 0.1457 | 0.1036 | 0.1199 | 0.2917 | 0.2131 | 0.244 |
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+ | 1.1175 | 4.0 | 43088 | 2.6382 | 0.3579 | 0.2618 | 0.2996 | 0.1488 | 0.106 | 0.1225 | 0.2956 | 0.2163 | 0.2475 |
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+ | 1.0102 | 5.0 | 53860 | 2.6818 | 0.3574 | 0.2609 | 0.2987 | 0.1478 | 0.1052 | 0.1217 | 0.2949 | 0.2154 | 0.2466 |
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+ | 0.9141 | 6.0 | 64632 | 2.7428 | 0.3571 | 0.2616 | 0.2992 | 0.148 | 0.1056 | 0.122 | 0.2938 | 0.2152 | 0.2461 |
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+ | 0.8261 | 7.0 | 75404 | 2.8255 | 0.3534 | 0.2582 | 0.2956 | 0.1457 | 0.1039 | 0.12 | 0.2906 | 0.2126 | 0.2432 |
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+ | 0.7509 | 8.0 | 86176 | 2.8975 | 0.3517 | 0.2572 | 0.2943 | 0.1428 | 0.1016 | 0.1175 | 0.289 | 0.2113 | 0.2418 |
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+ | 0.6822 | 9.0 | 96948 | 2.9586 | 0.3557 | 0.2599 | 0.2975 | 0.1466 | 0.1043 | 0.1206 | 0.2936 | 0.2145 | 0.2455 |
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+ | 0.6289 | 10.0 | 107720 | 3.0021 | 0.3553 | 0.2599 | 0.2974 | 0.1458 | 0.1039 | 0.12 | 0.2925 | 0.2139 | 0.2448 |
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  ### Framework versions
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