| | --- |
| | license: apache-2.0 |
| | base_model: google-t5/t5-small |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - lilferrit/xsum_t5_distillation |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: xsum_aligned_smallT5 |
| | results: |
| | - task: |
| | name: Summarization |
| | type: summarization |
| | dataset: |
| | name: lilferrit/xsum_t5_distillation |
| | type: lilferrit/xsum_t5_distillation |
| | metrics: |
| | - name: Rouge1 |
| | type: rouge |
| | value: 28.6381 |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # xsum_aligned_smallT5 |
| |
|
| | This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the lilferrit/xsum_t5_distillation dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.5258 |
| | - Rouge1: 28.6381 |
| | - Rouge2: 7.1512 |
| | - Rougel: 21.3477 |
| | - Rougelsum: 21.2928 |
| | - Gen Len: 27.92 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - training_steps: 200 |
| | |
| | ### Training results |
| | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| | |
