---
license: apache-2.0
base_model: buianh0803/text-sum-2
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: text-sum-3
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: test
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2475
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# text-sum-3

This model is a fine-tuned version of [buianh0803/text-sum-2](https://huggingface.co/buianh0803/text-sum-2) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6546
- Rouge1: 0.2475
- Rouge2: 0.1177
- Rougel: 0.2051
- Rougelsum: 0.2051
- 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: 0.001
- 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: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.8082        | 1.0   | 17945 | 1.6546          | 0.2475 | 0.1177 | 0.2051 | 0.2051    | 19.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1