---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: multinews_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: multi_news
      type: multi_news
      config: default
      split: test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.1482
---

<!-- 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. -->

# multinews_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7165
- Rouge1: 0.1482
- Rouge2: 0.0472
- Rougel: 0.1132
- Rougelsum: 0.1132
- 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 450  | 2.8616          | 0.1388 | 0.0418 | 0.1057 | 0.1056    | 19.0    |
| 3.2544        | 2.0   | 900  | 2.7991          | 0.1427 | 0.0438 | 0.1089 | 0.1089    | 19.0    |
| 2.999         | 3.0   | 1350 | 2.7693          | 0.1449 | 0.046  | 0.1115 | 0.1114    | 19.0    |
| 2.958         | 4.0   | 1800 | 2.7531          | 0.1466 | 0.0462 | 0.112  | 0.1118    | 19.0    |
| 2.9198        | 5.0   | 2250 | 2.7431          | 0.1466 | 0.0465 | 0.112  | 0.1119    | 19.0    |
| 2.8838        | 6.0   | 2700 | 2.7328          | 0.1474 | 0.0461 | 0.1125 | 0.1123    | 19.0    |
| 2.8774        | 7.0   | 3150 | 2.7270          | 0.1477 | 0.0463 | 0.1126 | 0.1124    | 19.0    |
| 2.8712        | 8.0   | 3600 | 2.7226          | 0.148  | 0.0466 | 0.1128 | 0.1127    | 19.0    |
| 2.854         | 9.0   | 4050 | 2.7197          | 0.1479 | 0.047  | 0.1129 | 0.1128    | 19.0    |
| 2.8541        | 10.0  | 4500 | 2.7188          | 0.1485 | 0.0471 | 0.113  | 0.1129    | 19.0    |
| 2.8541        | 11.0  | 4950 | 2.7168          | 0.1483 | 0.0472 | 0.1131 | 0.1131    | 19.0    |
| 2.8466        | 12.0  | 5400 | 2.7165          | 0.1482 | 0.0472 | 0.1132 | 0.1132    | 19.0    |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3