---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: cnn_news_summary_model_trained_on_reduced_data
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: train[:3%]
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.219
---

<!-- 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. -->

# cnn_news_summary_model_trained_on_reduced_data

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6041
- Rouge1: 0.219
- Rouge2: 0.0948
- Rougel: 0.1848
- Rougelsum: 0.1848
- 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:|
| No log        | 1.0   | 431  | 1.6223          | 0.2175 | 0.0939 | 0.1828 | 0.1829    | 19.0             |
| 1.9219        | 2.0   | 862  | 1.6070          | 0.2183 | 0.0942 | 0.184  | 0.1841    | 19.0             |
| 1.8272        | 3.0   | 1293 | 1.6041          | 0.219  | 0.0948 | 0.1848 | 0.1848    | 19.0             |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3