File size: 1,978 Bytes
f3d7aff |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: billsum-full-data
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: billsum
type: billsum
config: default
split: train[:95%]
args: default
metrics:
- name: Rouge1
type: rouge
value: 18.0383
---
<!-- 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. -->
# billsum-full-data
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6583
- Rouge1: 18.0383
- Rouge2: 14.8462
- Rougel: 17.6086
- Rougelsum: 17.6843
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.1401 | 1.0 | 8101 | 1.8087 | 17.8461 | 14.6015 | 17.3956 | 17.4842 |
| 1.7596 | 2.0 | 16202 | 1.6980 | 18.0568 | 14.7833 | 17.6068 | 17.6999 |
| 1.5789 | 3.0 | 24303 | 1.6583 | 18.0383 | 14.8462 | 17.6086 | 17.6843 |
### Framework versions
- Transformers 4.29.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3
|