File size: 3,907 Bytes
f37cbda e58e5db f37cbda e58e5db f37cbda e58e5db f37cbda e58e5db f37cbda 5aa0561 f37cbda |
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 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_oracle
metrics:
- rouge
model-index:
- name: bart_large_gov
results:
- task:
name: Summarization
type: summarization
dataset:
name: learn3r/gov_report_memsum_oracle
type: learn3r/gov_report_memsum_oracle
metrics:
- name: Rouge1
type: rouge
value: 71.9948
---
<!-- 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_large_gov
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the learn3r/gov_report_memsum_oracle dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4266
- Rouge1: 71.9948
- Rouge2: 41.0084
- Rougel: 38.0938
- Rougelsum: 69.4488
- Gen Len: 751.0288
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.7352 | 1.0 | 136 | 1.5224 | 72.0472 | 41.3267 | 36.4817 | 69.4011 | 685.9300 |
| 1.6874 | 1.99 | 272 | 1.4779 | 71.7737 | 40.8546 | 36.8472 | 69.2034 | 699.4866 |
| 1.5695 | 3.0 | 409 | 1.4583 | 72.2243 | 41.372 | 37.8382 | 69.6295 | 695.0977 |
| 1.4951 | 3.99 | 545 | 1.4495 | 71.5808 | 40.5556 | 37.152 | 69.0536 | 753.5967 |
| 1.496 | 5.0 | 682 | 1.4386 | 72.1271 | 41.1645 | 38.4096 | 69.6176 | 700.2160 |
| 1.4258 | 6.0 | 818 | 1.4374 | 71.9975 | 41.0013 | 37.9947 | 69.449 | 743.7068 |
| 1.4301 | 7.0 | 955 | 1.4296 | 71.8896 | 40.8303 | 38.346 | 69.357 | 724.5062 |
| 1.4015 | 8.0 | 1091 | 1.4313 | 72.0031 | 40.9229 | 38.2581 | 69.4154 | 731.2685 |
| 1.391 | 8.99 | 1227 | 1.4266 | 71.9948 | 41.0084 | 38.0938 | 69.4488 | 751.0288 |
| 1.3642 | 10.0 | 1364 | 1.4287 | 71.9115 | 40.8683 | 38.1602 | 69.3514 | 756.9568 |
| 1.3516 | 10.99 | 1500 | 1.4289 | 72.3822 | 41.5074 | 38.8088 | 69.8232 | 719.2798 |
| 1.3243 | 12.0 | 1637 | 1.4301 | 71.83 | 40.764 | 38.1124 | 69.2767 | 749.9475 |
| 1.3582 | 12.99 | 1773 | 1.4283 | 71.9495 | 40.9556 | 38.4201 | 69.4394 | 736.6698 |
| 1.3149 | 14.0 | 1910 | 1.4298 | 71.9599 | 40.8875 | 38.2722 | 69.4209 | 753.3230 |
| 1.288 | 15.0 | 2046 | 1.4326 | 72.1615 | 41.1549 | 38.611 | 69.5977 | 744.8858 |
| 1.2937 | 16.0 | 2183 | 1.4315 | 71.9783 | 40.9073 | 38.4263 | 69.4109 | 755.5340 |
| 1.258 | 17.0 | 2319 | 1.4328 | 72.0298 | 40.931 | 38.4845 | 69.4823 | 734.6399 |
| 1.2617 | 17.99 | 2455 | 1.4336 | 71.9488 | 40.8816 | 38.4521 | 69.4151 | 744.7068 |
| 1.2864 | 19.0 | 2592 | 1.4346 | 72.1334 | 40.9965 | 38.5682 | 69.5666 | 744.2449 |
| 1.2936 | 19.94 | 2720 | 1.4351 | 72.0397 | 40.9431 | 38.4161 | 69.5028 | 744.4588 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
|