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