| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | - summarization |
| | model-index: |
| | - name: bart-base-xsum |
| | results: |
| | - task: |
| | type: summarization |
| | name: Summarization |
| | dataset: |
| | name: xsum |
| | type: xsum |
| | config: default |
| | split: test |
| | metrics: |
| | - name: ROUGE-1 |
| | type: rouge |
| | value: 38.643 |
| | verified: true |
| | - name: ROUGE-2 |
| | type: rouge |
| | value: 17.7546 |
| | verified: true |
| | - name: ROUGE-L |
| | type: rouge |
| | value: 32.2114 |
| | verified: true |
| | - name: ROUGE-LSUM |
| | type: rouge |
| | value: 32.2207 |
| | verified: true |
| | - name: loss |
| | type: loss |
| | value: 1.8224396705627441 |
| | verified: true |
| | - name: gen_len |
| | type: gen_len |
| | value: 19.7028 |
| | verified: true |
| | - task: |
| | type: summarization |
| | name: Summarization |
| | dataset: |
| | name: xsum |
| | type: xsum |
| | config: default |
| | split: validation |
| | metrics: |
| | - name: ROUGE-1 |
| | type: rouge |
| | value: 38.7415 |
| | verified: true |
| | - name: ROUGE-2 |
| | type: rouge |
| | value: 17.8295 |
| | verified: true |
| | - name: ROUGE-L |
| | type: rouge |
| | value: 32.2861 |
| | verified: true |
| | - name: ROUGE-LSUM |
| | type: rouge |
| | value: 32.2763 |
| | verified: true |
| | - name: loss |
| | type: loss |
| | value: 1.8132821321487427 |
| | verified: true |
| | - name: gen_len |
| | type: gen_len |
| | value: 19.7116 |
| | verified: true |
| | dataset: |
| | type: |
| | xsum: null |
| | name: |
| | xsum: null |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # bart-base-xsum |
| |
|
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on [xsum](https://huggingface.co/datasets/xsum) dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8051 |
| | - R1: 0.5643 |
| | - R2: 0.3017 |
| | - Rl: 0.5427 |
| | - Rlsum: 0.5427 |
| |
|
| | ## 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: 5e-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 |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | R1 | R2 | Rl | Rlsum | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:| |
| | | 0.8983 | 1.0 | 6377 | 0.8145 | 0.5443 | 0.2724 | 0.5212 | 0.5211 | |
| | | 0.8211 | 2.0 | 12754 | 0.7940 | 0.5519 | 0.2831 | 0.5295 | 0.5295 | |
| | | 0.7701 | 3.0 | 19131 | 0.7839 | 0.5569 | 0.2896 | 0.5347 | 0.5348 | |
| | | 0.7046 | 4.0 | 25508 | 0.7792 | 0.5615 | 0.2956 | 0.5394 | 0.5393 | |
| | | 0.6837 | 5.0 | 31885 | 0.7806 | 0.5631 | 0.2993 | 0.5416 | 0.5416 | |
| | | 0.6412 | 6.0 | 38262 | 0.7816 | 0.5643 | 0.301 | 0.5427 | 0.5426 | |
| | | 0.6113 | 7.0 | 44639 | 0.7881 | 0.5645 | 0.3017 | 0.5428 | 0.5428 | |
| | | 0.5855 | 8.0 | 51016 | 0.7921 | 0.5651 | 0.303 | 0.5433 | 0.5432 | |
| | | 0.5636 | 9.0 | 57393 | 0.7972 | 0.5649 | 0.3032 | 0.5433 | 0.5433 | |
| | | 0.5482 | 10.0 | 63770 | 0.7996 | 0.565 | 0.3036 | 0.5436 | 0.5435 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.22.1 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.0.0 |
| | - Tokenizers 0.11.6 |
| | |
