| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: t5_small_A_SapBERT |
| | 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. --> |
| |
|
| | # t5_small_A_SapBERT |
| | |
| | This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8647 |
| | - Rouge1: 0.1085 |
| | - Rouge2: 0.0448 |
| | - Rougel: 0.1043 |
| | - Rougelsum: 0.1046 |
| | - Gen Len: 3.8938 |
| | |
| | ## 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: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 12 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | 3.034 | 1.0 | 527 | 1.1249 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| | | 1.0575 | 2.0 | 1054 | 1.0118 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | |
| | | 0.9878 | 3.0 | 1581 | 0.9322 | 0.0104 | 0.0058 | 0.0101 | 0.0101 | 0.5221 | |
| | | 0.8865 | 4.0 | 2108 | 0.9022 | 0.0363 | 0.0149 | 0.0349 | 0.0341 | 3.1681 | |
| | | 0.8832 | 5.0 | 2635 | 0.8891 | 0.0758 | 0.0303 | 0.0713 | 0.0715 | 3.9558 | |
| | | 0.8657 | 6.0 | 3162 | 0.8815 | 0.0955 | 0.041 | 0.0912 | 0.0924 | 4.292 | |
| | | 0.8153 | 7.0 | 3689 | 0.8753 | 0.1007 | 0.0439 | 0.0948 | 0.0957 | 3.9292 | |
| | | 0.8237 | 8.0 | 4216 | 0.8710 | 0.1063 | 0.0457 | 0.1006 | 0.1009 | 3.8319 | |
| | | 0.8491 | 9.0 | 4743 | 0.8681 | 0.103 | 0.0418 | 0.0982 | 0.0989 | 3.708 | |
| | | 0.8227 | 10.0 | 5270 | 0.8660 | 0.1085 | 0.0448 | 0.1043 | 0.1046 | 3.9027 | |
| | | 0.8355 | 11.0 | 5797 | 0.8649 | 0.1085 | 0.0448 | 0.1043 | 0.1046 | 3.8938 | |
| | | 0.7787 | 12.0 | 6324 | 0.8647 | 0.1085 | 0.0448 | 0.1043 | 0.1046 | 3.8938 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.1 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.10.1 |
| | - Tokenizers 0.13.2 |
| | |
