metadata
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: 56.2783
bart_large_gov
This model is a fine-tuned version of facebook/bart-large on the learn3r/gov_report_memsum_oracle dataset. It achieves the following results on the evaluation set:
- Loss: 1.4450
- Rouge1: 56.2783
- Rouge2: 31.1387
- Rougel: 39.2121
- Rougelsum: 51.8068
- Gen Len: 128.5062
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 |
|---|---|---|---|---|---|---|---|---|
| 1.6694 | 1.0 | 136 | 1.5338 | 54.2061 | 29.3577 | 37.2911 | 49.8337 | 139.7253 |
| 1.5178 | 1.99 | 272 | 1.4698 | 55.6621 | 30.6254 | 38.7491 | 51.2934 | 128.9475 |
| 1.4208 | 3.0 | 409 | 1.4487 | 55.4905 | 30.4201 | 38.412 | 51.1108 | 129.5658 |
| 1.3399 | 3.99 | 545 | 1.4450 | 56.2783 | 31.1387 | 39.2121 | 51.8068 | 128.5062 |
| 1.2326 | 5.0 | 682 | 1.4478 | 56.0182 | 30.7104 | 38.8337 | 51.6162 | 129.1358 |
| 1.1784 | 6.0 | 818 | 1.4533 | 56.4333 | 31.4483 | 39.5546 | 52.1347 | 128.7315 |
| 1.1739 | 7.0 | 955 | 1.4607 | 56.3636 | 31.1125 | 39.4055 | 51.9709 | 128.8241 |
| 1.1585 | 8.0 | 1091 | 1.4774 | 55.9356 | 30.7012 | 38.7824 | 51.5664 | 128.9640 |
| 1.0297 | 8.99 | 1227 | 1.4939 | 56.7487 | 31.552 | 39.6461 | 52.411 | 128.6553 |
| 1.0085 | 10.0 | 1364 | 1.5075 | 56.3918 | 31.2201 | 39.4213 | 51.9449 | 128.6265 |
| 0.9738 | 10.99 | 1500 | 1.5237 | 56.3041 | 30.9239 | 39.2625 | 51.8217 | 128.8282 |
| 0.9583 | 12.0 | 1637 | 1.5444 | 55.6539 | 30.2395 | 38.5901 | 51.1518 | 128.9136 |
| 0.9601 | 12.99 | 1773 | 1.5516 | 55.9154 | 30.5471 | 38.8607 | 51.2856 | 128.9784 |
| 0.8882 | 14.0 | 1910 | 1.5736 | 56.3282 | 30.9807 | 39.2351 | 51.8022 | 128.5206 |
| 0.851 | 15.0 | 2046 | 1.5891 | 56.0531 | 30.6748 | 38.8847 | 51.5739 | 128.7623 |
| 0.8825 | 16.0 | 2183 | 1.5978 | 56.0084 | 30.7943 | 38.9692 | 51.5587 | 128.7798 |
| 0.8169 | 17.0 | 2319 | 1.6076 | 55.8274 | 30.41 | 38.6258 | 51.3009 | 128.8632 |
| 0.8194 | 17.99 | 2455 | 1.6177 | 56.3214 | 30.9896 | 39.4754 | 51.9525 | 128.6461 |
| 0.8441 | 19.0 | 2592 | 1.6260 | 55.9842 | 30.6332 | 38.999 | 51.5685 | 128.8241 |
| 0.792 | 19.94 | 2720 | 1.6328 | 55.8983 | 30.5018 | 38.7764 | 51.3611 | 128.7407 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0