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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- id_liputan6 |
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model-index: |
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- name: bert2bert-model99-last |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert2bert-model99-last |
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This model is a fine-tuned version of [](https://huggingface.co/) on the id_liputan6 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8701 |
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- R1 Precision: 0.3001 |
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- R1 Recall: 0.34 |
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- R1 Fmeasure: 0.3156 |
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- R2 Precision: 0.121 |
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- R2 Recall: 0.1366 |
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- R2 Fmeasure: 0.1269 |
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- Rl Precision: 0.239 |
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- Rl Recall: 0.2707 |
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- Rl Fmeasure: 0.2513 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 18 |
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- eval_batch_size: 18 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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- mixed_precision_training: Native AMP |
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### Training results |
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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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| 2.3429 | 1.0 | 10772 | 2.7616 | 0.29 | 0.3334 | 0.3069 | 0.1175 | 0.1351 | 0.1243 | 0.2329 | 0.2678 | 0.2464 | |
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| 1.5227 | 2.0 | 21544 | 2.6637 | 0.287 | 0.3356 | 0.3062 | 0.1148 | 0.1338 | 0.1222 | 0.2304 | 0.2693 | 0.2457 | |
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| 1.3203 | 3.0 | 32316 | 2.6384 | 0.2934 | 0.3387 | 0.3111 | 0.1195 | 0.1377 | 0.1265 | 0.2355 | 0.272 | 0.2498 | |
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| 1.169 | 4.0 | 43088 | 2.6579 | 0.3004 | 0.3403 | 0.3158 | 0.1228 | 0.139 | 0.129 | 0.2407 | 0.2726 | 0.253 | |
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| 1.0416 | 5.0 | 53860 | 2.6894 | 0.2963 | 0.3367 | 0.3121 | 0.1202 | 0.1362 | 0.1264 | 0.2367 | 0.2691 | 0.2494 | |
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| 0.9303 | 6.0 | 64632 | 2.7418 | 0.2986 | 0.3417 | 0.3155 | 0.1213 | 0.1384 | 0.1279 | 0.2385 | 0.2727 | 0.2519 | |
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| 0.8375 | 7.0 | 75404 | 2.8060 | 0.3009 | 0.3417 | 0.3168 | 0.1223 | 0.1384 | 0.1285 | 0.2402 | 0.2727 | 0.2528 | |
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| 0.7675 | 8.0 | 86176 | 2.8701 | 0.3001 | 0.34 | 0.3156 | 0.121 | 0.1366 | 0.1269 | 0.239 | 0.2707 | 0.2513 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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