| | --- |
| | license: apache-2.0 |
| | base_model: t5-small |
| | tags: |
| | - summarization |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: t5-small-destination-inference |
| | 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-destination-inference |
| |
|
| | 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: 1.6668 |
| | - Rouge1: 25.6235 |
| | - Rouge2: 0.0 |
| | - Rougel: 25.6064 |
| | - Rougelsum: 25.6064 |
| |
|
| | ## 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: 5.6e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 8 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
| | | 2.6932 | 1.0 | 2927 | 2.0668 | 19.9009 | 0.0 | 19.9009 | 19.8838 | |
| | | 2.1793 | 2.0 | 5854 | 1.8923 | 22.2668 | 0.0 | 22.2583 | 22.2412 | |
| | | 2.0209 | 3.0 | 8781 | 1.8088 | 23.1807 | 0.0 | 23.1893 | 23.1978 | |
| | | 1.9254 | 4.0 | 11708 | 1.7439 | 24.5815 | 0.0 | 24.5815 | 24.5815 | |
| | | 1.8585 | 5.0 | 14635 | 1.7105 | 24.7865 | 0.0 | 24.7865 | 24.7865 | |
| | | 1.814 | 6.0 | 17562 | 1.6863 | 25.2989 | 0.0 | 25.316 | 25.2989 | |
| | | 1.781 | 7.0 | 20489 | 1.6730 | 25.3844 | 0.0 | 25.3844 | 25.3502 | |
| | | 1.7679 | 8.0 | 23416 | 1.6668 | 25.6235 | 0.0 | 25.6064 | 25.6064 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.0 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.14.1 |
| |
|
