| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - billsum |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: experiment-summarisation-2 |
| | 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: 0.1384 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # experiment-summarisation-2 |
| |
|
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the billsum dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.6952 |
| | - Rouge1: 0.1384 |
| | - Rouge2: 0.0422 |
| | - Rougel: 0.1089 |
| | - Rougelsum: 0.109 |
| | - 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: 4 |
| | - eval_batch_size: 4 |
| | - 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 | 248 | 3.1176 | 0.1349 | 0.0327 | 0.1088 | 0.109 | 19.0 | |
| | | No log | 2.0 | 496 | 2.7865 | 0.1333 | 0.0377 | 0.1072 | 0.1074 | 19.0 | |
| | | 7.2763 | 3.0 | 744 | 2.7115 | 0.1364 | 0.0406 | 0.1076 | 0.1078 | 19.0 | |
| | | 7.2763 | 4.0 | 992 | 2.6952 | 0.1384 | 0.0422 | 0.1089 | 0.109 | 19.0 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| |
|
