transformers safetensors bart text2text-generation generated_from_trainer dataset:learn3r/gov_report_memsum_oracle base_model:facebook/bart-large base_model:finetune:facebook/bart-large license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-large
datasets:
- learn3r/gov_report_memsum_oracle
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart_large_gov
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: learn3r/gov_report_memsum_oracle
      type: learn3r/gov_report_memsum_oracle
    metrics:
    - type: rouge
      value: 71.9948
      name: Rouge1
---

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# 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
