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---
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- summarization
- generated_from_trainer
datasets:
- gov_report_summarization_dataset
metrics:
- rouge
model-index:
- name: long-t5-tglobal-base-finetuned-govReport-4096
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gov_report_summarization_dataset
type: gov_report_summarization_dataset
config: document
split: validation
args: document
metrics:
- name: Rouge1
type: rouge
value: 0.0463
---
<!-- 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. -->
# long-t5-tglobal-base-finetuned-govReport-4096
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the gov_report_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3116
- Rouge1: 0.0463
- Rouge2: 0.0231
- Rougel: 0.039
- Rougelsum: 0.0436
## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 14.9489 | 1.0 | 25 | 2.8019 | 0.0416 | 0.0156 | 0.0343 | 0.0383 |
| 3.9751 | 2.0 | 50 | 2.0899 | 0.0396 | 0.0145 | 0.0332 | 0.0367 |
| 3.0361 | 3.0 | 75 | 1.4337 | 0.0395 | 0.0138 | 0.033 | 0.0366 |
| 1.8477 | 4.0 | 100 | 1.3654 | 0.0406 | 0.0157 | 0.0342 | 0.0378 |
| 1.6709 | 5.0 | 125 | 1.3355 | 0.0419 | 0.0171 | 0.036 | 0.0394 |
| 1.5673 | 6.0 | 150 | 1.3229 | 0.0446 | 0.022 | 0.0383 | 0.0423 |
| 1.5567 | 7.0 | 175 | 1.3181 | 0.047 | 0.0233 | 0.0393 | 0.0441 |
| 1.5066 | 8.0 | 200 | 1.3135 | 0.0467 | 0.0233 | 0.0394 | 0.0441 |
| 1.515 | 9.0 | 225 | 1.3117 | 0.0462 | 0.0231 | 0.0389 | 0.0436 |
| 1.4868 | 10.0 | 250 | 1.3116 | 0.0463 | 0.0231 | 0.039 | 0.0436 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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