| | --- |
| | license: apache-2.0 |
| | base_model: t5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: cdc_influenza |
| | 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. --> |
| |
|
| | # cdc_influenza |
| | |
| | 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: 0.7083 |
| | - Rouge1: 0.2081 |
| | - Rouge2: 0.0515 |
| | - Rougel: 0.1688 |
| | - Rougelsum: 0.1681 |
| | - 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: 32 |
| | - eval_batch_size: 32 |
| | - 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 | 3 | 0.7952 | 0.2523 | 0.0973 | 0.2044 | 0.2089 | 19.0 | |
| | | No log | 2.0 | 6 | 0.7487 | 0.2258 | 0.0711 | 0.1855 | 0.1841 | 19.0 | |
| | | No log | 3.0 | 9 | 0.7204 | 0.2081 | 0.0515 | 0.1688 | 0.1681 | 19.0 | |
| | | No log | 4.0 | 12 | 0.7083 | 0.2081 | 0.0515 | 0.1688 | 0.1681 | 19.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
