---
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LongT5-Base-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-Base-NSPCC

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1612
- Rouge1: 0.4604
- Rouge2: 0.1738
- Rougel: 0.2641
- Rougelsum: 0.2648
- Gen Len: 242.1064

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 13.1772       | 1.0   | 12   | 2.8918          | 0.2996 | 0.0788 | 0.1529 | 0.1528    | 359.617  |
| 2.3541        | 2.0   | 24   | 1.2767          | 0.3935 | 0.1207 | 0.1972 | 0.1965    | 340.8298 |
| 1.5574        | 3.0   | 36   | 1.1901          | 0.4486 | 0.1662 | 0.2444 | 0.2444    | 278.3511 |
| 1.439         | 4.0   | 48   | 1.1712          | 0.46   | 0.1746 | 0.2628 | 0.2636    | 254.266  |
| 1.4027        | 5.0   | 60   | 1.1603          | 0.4625 | 0.174  | 0.2619 | 0.2622    | 246.0851 |
| 1.3858        | 6.0   | 72   | 1.1612          | 0.4604 | 0.1738 | 0.2641 | 0.2648    | 242.1064 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2