| | --- |
| | license: apache-2.0 |
| | base_model: t5-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: T5_base_NASA_ADS_title_v5 |
| | 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_base_NASA_ADS_title_v5 |
| | |
| | This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.7910 |
| | - Rouge1: 0.4285 |
| | - Rouge2: 0.2147 |
| | - Rougel: 0.3712 |
| | - Rougelsum: 0.3711 |
| | - Gen Len: 16.3966 |
| | |
| | ## 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: 15 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | 2.1209 | 1.0 | 2535 | 1.9129 | 0.4133 | 0.2034 | 0.3581 | 0.3581 | 16.0037 | |
| | | 1.9984 | 2.0 | 5070 | 1.8568 | 0.4138 | 0.2051 | 0.3608 | 0.3608 | 15.9065 | |
| | | 1.9004 | 3.0 | 7605 | 1.8307 | 0.4222 | 0.2109 | 0.3675 | 0.3674 | 15.9252 | |
| | | 1.8491 | 4.0 | 10140 | 1.8110 | 0.4199 | 0.209 | 0.3638 | 0.3638 | 16.1813 | |
| | | 1.7823 | 5.0 | 12675 | 1.7972 | 0.4231 | 0.2107 | 0.3665 | 0.3664 | 16.2793 | |
| | | 1.7302 | 6.0 | 15210 | 1.7924 | 0.427 | 0.2145 | 0.3704 | 0.3705 | 16.3819 | |
| | | 1.6996 | 7.0 | 17745 | 1.7918 | 0.4284 | 0.2157 | 0.3712 | 0.3713 | 16.0767 | |
| | | 1.6705 | 8.0 | 20280 | 1.7851 | 0.4252 | 0.2134 | 0.3682 | 0.3682 | 16.3485 | |
| | | 1.6338 | 9.0 | 22815 | 1.7853 | 0.4291 | 0.2146 | 0.3721 | 0.372 | 16.398 | |
| | | 1.6193 | 10.0 | 25350 | 1.7850 | 0.4297 | 0.2158 | 0.3726 | 0.3725 | 16.3821 | |
| | | 1.5808 | 11.0 | 27885 | 1.7837 | 0.4274 | 0.2144 | 0.3708 | 0.3706 | 16.303 | |
| | | 1.574 | 12.0 | 30420 | 1.7895 | 0.428 | 0.2151 | 0.3708 | 0.3709 | 16.3568 | |
| | | 1.5544 | 13.0 | 32955 | 1.7898 | 0.4282 | 0.2152 | 0.3711 | 0.3711 | 16.412 | |
| | | 1.5377 | 14.0 | 35490 | 1.7902 | 0.4287 | 0.2147 | 0.3709 | 0.3709 | 16.3917 | |
| | | 1.5304 | 15.0 | 38025 | 1.7910 | 0.4285 | 0.2147 | 0.3712 | 0.3711 | 16.3966 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.0 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.19.1 |
| | |
