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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: bert2bert_law_summarization_tr |
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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_law_summarization_tr |
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This model is a fine-tuned version of [mrm8488/bert2bert_shared-turkish-summarization](https://huggingface.co/mrm8488/bert2bert_shared-turkish-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9682 |
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- Rouge1: 0.6221 |
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- Rouge2: 0.5799 |
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- Rougel: 0.6007 |
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- Rougelsum: 0.6009 |
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- Gen Len: 63.3077 |
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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: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: 4 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 1.6025 | 1.0 | 520 | 1.1210 | 0.611 | 0.5687 | 0.5885 | 0.5883 | 62.6154 | |
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| 1.0845 | 2.0 | 1040 | 1.0161 | 0.62 | 0.5789 | 0.601 | 0.6005 | 63.4038 | |
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| 0.9252 | 3.0 | 1560 | 0.9784 | 0.6249 | 0.583 | 0.6043 | 0.6045 | 63.2654 | |
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| 0.858 | 4.0 | 2080 | 0.9682 | 0.6221 | 0.5799 | 0.6007 | 0.6009 | 63.3077 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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