| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: ru_t5model_for_legalsimplification |
| 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. --> |
|
|
| # ru_t5model_for_legalsimplification |
| |
| This model is a fine-tuned version of [IlyaGusev/rut5_base_sum_gazeta](https://huggingface.co/IlyaGusev/rut5_base_sum_gazeta) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: nan |
| - Rouge1: 0.5364 |
| - Rouge2: 0.1481 |
| - Rougel: 0.506 |
| - Rougelsum: 0.4917 |
| - Gen Len: 163.03 |
| |
| ## 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: 0.002 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 157 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | No log | 2.0 | 314 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | No log | 3.0 | 471 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 4.0 | 628 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 5.0 | 785 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 6.0 | 942 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 7.0 | 1099 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 8.0 | 1256 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 9.0 | 1413 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| | 0.0 | 10.0 | 1570 | nan | 0.5364 | 0.1481 | 0.506 | 0.4917 | 163.03 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.22.2 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.1 |
| - Tokenizers 0.12.1 |
| |
