| | --- |
| | license: apache-2.0 |
| | base_model: t5-small |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - billsum |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: test_trainer |
| | results: |
| | - task: |
| | name: Sequence-to-sequence Language Modeling |
| | type: text2text-generation |
| | dataset: |
| | name: billsum |
| | type: billsum |
| | config: default |
| | split: ca_test |
| | args: default |
| | metrics: |
| | - name: Rouge1 |
| | type: rouge |
| | value: 0.1416 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # test_trainer |
| | |
| | This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.5392 |
| | - Rouge1: 0.1416 |
| | - Rouge2: 0.0487 |
| | - Rougel: 0.1147 |
| | - Rougelsum: 0.1146 |
| | - 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: 4 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | No log | 1.0 | 62 | 2.8306 | 0.1276 | 0.0376 | 0.1061 | 0.1064 | 19.0 | |
| | | No log | 2.0 | 124 | 2.6198 | 0.1367 | 0.0468 | 0.1118 | 0.1117 | 19.0 | |
| | | No log | 3.0 | 186 | 2.5563 | 0.1409 | 0.0488 | 0.1144 | 0.1145 | 19.0 | |
| | | No log | 4.0 | 248 | 2.5392 | 0.1416 | 0.0487 | 0.1147 | 0.1146 | 19.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.1 |
| | - Pytorch 2.0.0 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
