| --- |
| license: apache-2.0 |
| base_model: stevhliu/my_awesome_billsum_model |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: Modelo_Resumen |
| 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. --> |
|
|
| # Modelo_Resumen |
| |
| Éste modelo fue creado para la clase del Dr. Gendry |
| - Loss: 2.2007 |
| - Rouge1: 0.1957 |
| - Rouge2: 0.095 |
| - Rougel: 0.1645 |
| - Rougelsum: 0.1645 |
| - Gen Len: 19.0 |
| |
| ## 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: 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: 15 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | No log | 1.0 | 62 | 2.3594 | 0.1957 | 0.0921 | 0.1645 | 0.1645 | 19.0 | |
| | No log | 2.0 | 124 | 2.3268 | 0.194 | 0.0898 | 0.1631 | 0.1631 | 19.0 | |
| | No log | 3.0 | 186 | 2.3013 | 0.194 | 0.0923 | 0.1649 | 0.1648 | 19.0 | |
| | No log | 4.0 | 248 | 2.2776 | 0.195 | 0.0932 | 0.166 | 0.1659 | 19.0 | |
| | No log | 5.0 | 310 | 2.2620 | 0.1944 | 0.0925 | 0.165 | 0.1649 | 19.0 | |
| | No log | 6.0 | 372 | 2.2474 | 0.1935 | 0.0917 | 0.1648 | 0.1646 | 19.0 | |
| | No log | 7.0 | 434 | 2.2362 | 0.1931 | 0.0929 | 0.1642 | 0.1642 | 19.0 | |
| | No log | 8.0 | 496 | 2.2276 | 0.1937 | 0.0935 | 0.1642 | 0.1644 | 19.0 | |
| | 2.4678 | 9.0 | 558 | 2.2203 | 0.1941 | 0.0938 | 0.164 | 0.164 | 19.0 | |
| | 2.4678 | 10.0 | 620 | 2.2141 | 0.195 | 0.0954 | 0.1648 | 0.1648 | 19.0 | |
| | 2.4678 | 11.0 | 682 | 2.2095 | 0.1956 | 0.096 | 0.1649 | 0.1649 | 19.0 | |
| | 2.4678 | 12.0 | 744 | 2.2055 | 0.1952 | 0.0955 | 0.1645 | 0.1645 | 19.0 | |
| | 2.4678 | 13.0 | 806 | 2.2030 | 0.1945 | 0.0947 | 0.1639 | 0.1638 | 19.0 | |
| | 2.4678 | 14.0 | 868 | 2.2014 | 0.1956 | 0.095 | 0.1644 | 0.1644 | 19.0 | |
| | 2.4678 | 15.0 | 930 | 2.2007 | 0.1957 | 0.095 | 0.1645 | 0.1645 | 19.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
| |
