|
--- |
|
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 |
|
|
