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---
license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_bp
metrics:
- rouge
model-index:
- name: longt5_xl_gov_memsum_bp_5
results:
- task:
name: Summarization
type: summarization
dataset:
name: learn3r/gov_report_memsum_bp
type: learn3r/gov_report_memsum_bp
metrics:
- name: Rouge1
type: rouge
value: 55.1149
---
<!-- 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. -->
# longt5_xl_gov_memsum_bp_5
This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/gov_report_memsum_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9813
- Rouge1: 55.1149
- Rouge2: 30.149
- Rougel: 31.9694
- Rougelsum: 52.9549
- Gen Len: 1101.6060
## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:---------:|
| 1.1562 | 1.0 | 272 | 1.0105 | 37.2934 | 18.6683 | 24.0563 | 35.6575 | 1844.1543 |
| 0.9737 | 2.0 | 545 | 0.9813 | 55.1149 | 30.149 | 31.9694 | 52.9549 | 1101.6060 |
| 0.8395 | 3.0 | 818 | 0.9925 | 57.4498 | 31.9315 | 32.914 | 55.2389 | 1055.9784 |
| 0.7353 | 4.0 | 1091 | 1.0404 | 67.3946 | 39.2034 | 36.8583 | 64.9879 | 829.2881 |
| 0.6212 | 4.99 | 1360 | 1.0752 | 64.5433 | 36.9477 | 35.3482 | 62.2005 | 779.6152 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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