bert2bert-model0 / README.md
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---
tags:
- generated_from_trainer
datasets:
- id_liputan6
model-index:
- name: bert2bert-dropout-0.3-lr-5e-05-ds-canonical
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-dropout-0.3-lr-5e-05-ds-canonical
This model was trained from scratch on the id_liputan6 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2037
- Rouge2 Precision: 0.1783
- Rouge2 Recall: 0.1901
- Rouge2 Fmeasure: 0.1818
## 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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 1.7398 | 1.0 | 4040 | 2.2892 | 0.1789 | 0.1933 | 0.1835 |
| 1.5953 | 2.0 | 8080 | 2.2380 | 0.1789 | 0.1917 | 0.1829 |
| 1.5771 | 3.0 | 12120 | 2.2037 | 0.1783 | 0.1901 | 0.1818 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1