---
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: 1.5481
- Rouge1: 0.4597
- Rouge2: 0.1665
- Rougel: 0.2562
- Rougelsum: 0.2557
- Gen Len: 250.6383

## 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 6.0521        | 1.0   | 188  | 2.8154          | 0.2268 | 0.0411 | 0.1627 | 0.1626    | 145.7447 |
| 2.5796        | 2.0   | 377  | 1.9961          | 0.3798 | 0.1115 | 0.2103 | 0.2101    | 220.234  |
| 2.0398        | 3.0   | 566  | 1.7703          | 0.4208 | 0.1319 | 0.2255 | 0.2258    | 299.6915 |
| 1.7329        | 4.0   | 755  | 1.5996          | 0.4427 | 0.1488 | 0.2423 | 0.2424    | 255.2553 |
| 1.5609        | 5.0   | 943  | 1.5510          | 0.4688 | 0.1726 | 0.2578 | 0.2576    | 289.2979 |
| 1.4733        | 5.98  | 1128 | 1.5481          | 0.4597 | 0.1665 | 0.2562 | 0.2557    | 250.6383 |


### Framework versions

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