---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- arxiv-summarization
metrics:
- rouge
model-index:
- name: t5-base-axriv-to-abstract-3
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: arxiv-summarization
      type: arxiv-summarization
      config: section
      split: validation
      args: section
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.1301
---

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# t5-base-axriv-to-abstract-3

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6588
- Rouge1: 0.1301
- Rouge2: 0.0481
- Rougel: 0.1047
- Rougelsum: 0.1047
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5634        | 0.61  | 4000  | 2.4010          | 0.1339 | 0.0519 | 0.1074 | 0.1075    | 19.0    |
| 2.4533        | 1.21  | 8000  | 2.3582          | 0.1318 | 0.0517 | 0.1067 | 0.1067    | 19.0    |
| 3.0109        | 1.82  | 12000 | 2.7488          | 0.1366 | 0.0509 | 0.1096 | 0.1095    | 18.9963 |
| 2.9063        | 2.42  | 16000 | 2.6588          | 0.1301 | 0.0481 | 0.1047 | 0.1047    | 19.0    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3