metadata
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bert2bert_law_summarization
results: []
bert2bert_law_summarization
This model is a fine-tuned version of mrm8488/bert2bert_shared-turkish-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1184
- Rouge1: 0.6064
- Rouge2: 0.5608
- Rougel: 0.5828
- Rougelsum: 0.5836
- Gen Len: 63.2615
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.5546 | 1.0 | 520 | 1.2699 | 0.6047 | 0.5588 | 0.5795 | 0.5799 | 62.7038 |
1.071 | 2.0 | 1040 | 1.1607 | 0.6075 | 0.5598 | 0.5814 | 0.5824 | 63.2269 |
0.9101 | 3.0 | 1560 | 1.1268 | 0.6129 | 0.569 | 0.5884 | 0.5891 | 62.9654 |
0.798 | 4.0 | 2080 | 1.1184 | 0.6064 | 0.5608 | 0.5828 | 0.5836 | 63.2615 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3