| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: t5small_contracts |
| | 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. --> |
| |
|
| | # t5small_contracts |
| | |
| | This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.9521 |
| | - Rouge1: 0.2926 |
| | - Rouge2: 0.1622 |
| | - Rougel: 0.2568 |
| | - Rougelsum: 0.2549 |
| | - Gen Len: 18.4146 |
| | |
| | ## 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 | 11 | 3.3928 | 0.2931 | 0.1602 | 0.2571 | 0.255 | 18.5122 | |
| | | No log | 2.0 | 22 | 3.1343 | 0.2951 | 0.1632 | 0.2593 | 0.2565 | 18.4146 | |
| | | No log | 3.0 | 33 | 3.0073 | 0.2919 | 0.1617 | 0.2563 | 0.2541 | 18.4146 | |
| | | No log | 4.0 | 44 | 2.9521 | 0.2926 | 0.1622 | 0.2568 | 0.2549 | 18.4146 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.1 |
| | - Pytorch 1.13.1 |
| | - Datasets 2.10.0 |
| | - Tokenizers 0.11.0 |
| | |
