| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - xsum | |
| metrics: | |
| - rouge | |
| base_model: google/flan-t5-base | |
| model-index: | |
| - name: flan-t5-base-xsum | |
| results: | |
| - task: | |
| type: text2text-generation | |
| name: Sequence-to-sequence Language Modeling | |
| dataset: | |
| name: xsum | |
| type: xsum | |
| config: default | |
| split: test | |
| args: default | |
| metrics: | |
| - type: rouge | |
| value: 32.3503 | |
| name: Rouge1 | |
| <!-- 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. --> | |
| # flan-t5-base-xsum | |
| This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the xsum dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 2.0798 | |
| - Rouge1: 32.3503 | |
| - Rouge2: 10.8909 | |
| - Rougel: 25.9346 | |
| - Rougelsum: 25.9216 | |
| - Gen Len: 18.8494 | |
| ## 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: 0.0005 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adafactor | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| | |
| | 2.335 | 1.0 | 1417 | 2.0823 | 31.3453 | 10.2077 | 25.0051 | 25.008 | 18.8259 | | |
| | 1.8642 | 2.0 | 2834 | 2.0798 | 32.3503 | 10.8909 | 25.9346 | 25.9216 | 18.8494 | | |
| | 1.5208 | 3.0 | 4251 | 2.1272 | 32.6743 | 11.3394 | 26.3776 | 26.3724 | 18.8435 | | |
| | 1.2628 | 4.0 | 5668 | 2.2110 | 32.695 | 11.3273 | 26.3215 | 26.322 | 18.8306 | | |
| | 1.0649 | 5.0 | 7085 | 2.3143 | 32.5287 | 11.3662 | 26.274 | 26.2741 | 18.8345 | | |
| ### Framework versions | |
| - Transformers 4.26.1 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.10.0 | |
| - Tokenizers 0.13.2 | |