---
license: apache-2.0
base_model: google/long-t5-tglobal-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LongT5-Large-NSPCC
  results: []
---

<!-- 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-Large-NSPCC

This model is a fine-tuned version of [google/long-t5-tglobal-large](https://huggingface.co/google/long-t5-tglobal-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3710
- Rouge1: 0.4978
- Rouge2: 0.2091
- Rougel: 0.2874
- Rougelsum: 0.2871
- Gen Len: 251.3511

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 6.0401        | 0.9960 | 188  | 2.7089          | 0.2766 | 0.0617 | 0.1655 | 0.1657    | 151.7021 |
| 2.4805        | 1.9974 | 377  | 1.8809          | 0.382  | 0.1178 | 0.2092 | 0.2092    | 211.1809 |
| 1.8093        | 2.9987 | 566  | 1.5769          | 0.4356 | 0.1527 | 0.2409 | 0.2409    | 246.1277 |
| 1.4653        | 4.0    | 755  | 1.4359          | 0.4661 | 0.1722 | 0.26   | 0.2603    | 245.0851 |
| 1.2626        | 4.9960 | 943  | 1.3908          | 0.4829 | 0.1931 | 0.2717 | 0.2717    | 239.8617 |
| 1.117         | 5.9974 | 1132 | 1.3724          | 0.4864 | 0.1988 | 0.2804 | 0.2804    | 244.4255 |
| 1.0404        | 6.9987 | 1321 | 1.3714          | 0.4914 | 0.2007 | 0.2826 | 0.2821    | 248.6915 |
| 1.0065        | 7.9682 | 1504 | 1.3710          | 0.4978 | 0.2091 | 0.2874 | 0.2871    | 251.3511 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1