---
library_name: transformers
license: apache-2.0
base_model: gsarti/it5-small-news-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: news_summary_model_trained_on_reduced_data
  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. -->

# news_summary_model_trained_on_reduced_data

This model is a fine-tuned version of [gsarti/it5-small-news-summarization](https://huggingface.co/gsarti/it5-small-news-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.1141
- Rouge2: 0.0402
- Rougel: 0.1005
- Rougelsum: 0.1018
- Generated Length: 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 | Generated Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:|
| No log        | 1.0   | 9    | nan             | 0.1141 | 0.0402 | 0.1005 | 0.1018    | 19.0             |
| No log        | 2.0   | 18   | nan             | 0.1141 | 0.0402 | 0.1005 | 0.1018    | 19.0             |
| No log        | 3.0   | 27   | nan             | 0.1141 | 0.0402 | 0.1005 | 0.1018    | 19.0             |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1