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--- |
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license: apache-2.0 |
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base_model: allenai/led-base-16384 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- billsum |
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metrics: |
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- rouge |
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model-index: |
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- name: LED_billsum_model |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: billsum |
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type: billsum |
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config: default |
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split: ca_test |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.1447 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# LED_billsum_model |
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This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the billsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6576 |
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- Rouge1: 0.1447 |
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- Rouge2: 0.0854 |
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- Rougel: 0.1292 |
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- Rougelsum: 0.1339 |
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- Gen Len: 20.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 1.4849 | 1.0 | 330 | 1.6511 | 0.1463 | 0.0827 | 0.1276 | 0.1337 | 20.0 | |
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| 1.3361 | 2.0 | 660 | 1.6056 | 0.148 | 0.0799 | 0.1268 | 0.1336 | 20.0 | |
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| 1.1727 | 3.0 | 990 | 1.5833 | 0.1459 | 0.0827 | 0.1289 | 0.1341 | 20.0 | |
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| 1.0601 | 4.0 | 1320 | 1.5987 | 0.1462 | 0.0859 | 0.1299 | 0.1344 | 20.0 | |
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| 0.9789 | 5.0 | 1650 | 1.6030 | 0.1414 | 0.0794 | 0.125 | 0.1302 | 20.0 | |
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| 0.8724 | 6.0 | 1980 | 1.6060 | 0.1476 | 0.0868 | 0.1298 | 0.1356 | 20.0 | |
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| 0.7994 | 7.0 | 2310 | 1.6295 | 0.1348 | 0.0758 | 0.1198 | 0.1253 | 20.0 | |
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| 0.7762 | 8.0 | 2640 | 1.6317 | 0.1422 | 0.0831 | 0.1261 | 0.1312 | 20.0 | |
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| 0.7087 | 9.0 | 2970 | 1.6501 | 0.1421 | 0.0825 | 0.1264 | 0.1311 | 20.0 | |
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| 0.7014 | 10.0 | 3300 | 1.6576 | 0.1447 | 0.0854 | 0.1292 | 0.1339 | 20.0 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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