---
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: 0.7756
- Rouge1: 0.5243
- Rouge2: 0.242
- Rougel: 0.3113
- Rougelsum: 0.3122
- Gen Len: 331.8511

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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  |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 4.0417        | 0.9947 | 94   | 0.8455          | 0.4707 | 0.1986 | 0.2704 | 0.2718    | 303.4468 |
| 1.0117        | 2.0    | 189  | 0.8058          | 0.5178 | 0.239  | 0.3066 | 0.3077    | 326.3085 |
| 0.886         | 2.9947 | 283  | 0.7798          | 0.5085 | 0.2272 | 0.298  | 0.2989    | 348.7979 |
| 0.805         | 4.0    | 378  | 0.7725          | 0.5194 | 0.2386 | 0.309  | 0.31      | 331.3191 |
| 0.7724        | 4.9947 | 472  | 0.7749          | 0.5224 | 0.2423 | 0.3133 | 0.3147    | 333.6489 |
| 0.7514        | 5.9683 | 564  | 0.7756          | 0.5243 | 0.242  | 0.3113 | 0.3122    | 331.8511 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1