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---
license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
- generated_from_trainer
datasets:
- tau/scrolls
metrics:
- rouge
model-index:
- name: longt5_xl_gov_5
results:
- task:
name: Summarization
type: summarization
dataset:
name: tau/scrolls gov_report
type: tau/scrolls
config: gov_report
split: validation
args: gov_report
metrics:
- name: Rouge1
type: rouge
value: 54.2522
---
<!-- 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_5
This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the tau/scrolls gov_report dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4141
- Rouge1: 54.2522
- Rouge2: 24.7528
- Rougel: 27.2444
- Rougelsum: 51.5916
- Gen Len: 889.25
## 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: 128
- total_train_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.6209 | 1.0 | 136 | 1.5434 | 45.0062 | 18.1618 | 23.3808 | 41.7616 | 904.1996 |
| 1.418 | 1.99 | 272 | 1.4141 | 54.2522 | 24.7528 | 27.2444 | 51.5916 | 889.25 |
| 1.2626 | 3.0 | 409 | 1.4249 | 52.4332 | 23.708 | 27.2902 | 49.8071 | 878.4095 |
| 1.0992 | 4.0 | 545 | 1.4211 | 55.2041 | 26.5229 | 29.9951 | 52.6487 | 670.7047 |
| 0.9974 | 4.99 | 680 | 1.4569 | 55.9961 | 26.2205 | 29.0409 | 53.3109 | 883.0463 |
### Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
|