initial commit bert2bert-model99-last-Xtreme-Train

README.md

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+---
+base_model: Alfahluzi/bert2bert-model99-last
+tags:
+- generated_from_trainer
+datasets:
+- id_liputan6
+model-index:
+- name: bert2bert-model99-last-Xtreme-Train
+  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-Xtreme-Train
+
+This model is a fine-tuned version of [Alfahluzi/bert2bert-model99-last](https://huggingface.co/Alfahluzi/bert2bert-model99-last) on the id_liputan6 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8449
+- R1 Precision: 0.3481
+- R1 Recall: 0.3462
+- R1 Fmeasure: 0.3448
+- R2 Precision: 0.1475
+- R2 Recall: 0.1463
+- R2 Fmeasure: 0.1458
+- Rl Precision: 0.2761
+- Rl Recall: 0.2748
+- Rl Fmeasure: 0.2736
+
+## 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: 10
+- eval_batch_size: 10
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|:------------:|:---------:|:-----------:|
+| 2.5931        | 1.0   | 495  | 2.3625          | 0.359        | 0.3516    | 0.3528      | 0.159        | 0.155     | 0.1557      | 0.2876       | 0.2819    | 0.2826      |
+| 1.8329        | 2.0   | 990  | 2.4301          | 0.3577       | 0.3489    | 0.3508      | 0.1563       | 0.1517    | 0.1528      | 0.286        | 0.2793    | 0.2806      |
+| 1.3237        | 3.0   | 1485 | 2.6019          | 0.3483       | 0.3445    | 0.344       | 0.149        | 0.1468    | 0.1468      | 0.2784       | 0.2755    | 0.275       |
+| 0.976         | 4.0   | 1980 | 2.7468          | 0.3509       | 0.3481    | 0.3471      | 0.1501       | 0.1483    | 0.1481      | 0.2784       | 0.2765    | 0.2755      |
+| 0.7665        | 5.0   | 2475 | 2.8449          | 0.3481       | 0.3462    | 0.3448      | 0.1475       | 0.1463    | 0.1458      | 0.2761       | 0.2748    | 0.2736      |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "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": "4.38.2"
+}

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