| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - billsum | |
| metrics: | |
| - rouge | |
| base_model: t5-small | |
| model-index: | |
| - name: txt_summary_model | |
| results: | |
| - task: | |
| type: text2text-generation | |
| name: Sequence-to-sequence Language Modeling | |
| dataset: | |
| name: billsum | |
| type: billsum | |
| config: default | |
| split: ca_test | |
| args: default | |
| metrics: | |
| - type: rouge | |
| value: 0.1389 | |
| name: Rouge1 | |
| <!-- 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. --> | |
| # txt_summary_model | |
| 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: 2.5514 | |
| - Rouge1: 0.1389 | |
| - Rouge2: 0.0536 | |
| - Rougel: 0.1181 | |
| - Rougelsum: 0.1176 | |
| - 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 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | |
| | No log | 1.0 | 62 | 2.8496 | 0.1231 | 0.0345 | 0.1031 | 0.103 | 19.0 | | |
| | No log | 2.0 | 124 | 2.6339 | 0.1302 | 0.0452 | 0.1107 | 0.1105 | 19.0 | | |
| | No log | 3.0 | 186 | 2.5686 | 0.1373 | 0.0518 | 0.1163 | 0.1158 | 19.0 | | |
| | No log | 4.0 | 248 | 2.5514 | 0.1389 | 0.0536 | 0.1181 | 0.1176 | 19.0 | | |
| ### Framework versions | |
| - Transformers 4.29.2 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |