train 8 epochs with 18 batch size

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- id_liputan6
+model-index:
+- name: bert2bert-model99-last
+  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-model99-last
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the id_liputan6 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8701
+- R1 Precision: 0.3001
+- R1 Recall: 0.34
+- R1 Fmeasure: 0.3156
+- R2 Precision: 0.121
+- R2 Recall: 0.1366
+- R2 Fmeasure: 0.1269
+- Rl Precision: 0.239
+- Rl Recall: 0.2707
+- Rl Fmeasure: 0.2513
+
+## 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: 8
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
+| 2.3429        | 1.0   | 10772 | 2.7616          | 0.29         | 0.3334    | 0.3069      | 0.1175       | 0.1351    | 0.1243      | 0.2329       | 0.2678    | 0.2464      |
+| 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      |
+| 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      |
+| 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       |
+| 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      |
+| 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      |
+| 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      |
+| 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      |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1
+- Datasets 2.19.0
+- Tokenizers 0.19.1

generation_config.json

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+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 3,
+  "early_stopping": true,
+  "eos_token_id": 4,
+  "length_penalty": 2.0,
+  "max_length": 80,
+  "min_length": 10,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 10,
+  "pad_token_id": 0,
+  "transformers_version": "4.40.0"
+}