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buianh0803
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text-sum-2

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
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text-sum-2
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---
license: apache-2.0
base_model: buianh0803/text-sum
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: text-sum-2
  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: 0.2485
---

<!-- 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. -->

# text-sum-2

This model is a fine-tuned version of [buianh0803/text-sum](https://huggingface.co/buianh0803/text-sum) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6574
- Rouge1: 0.2485
- Rouge2: 0.1188
- Rougel: 0.2056
- Rougelsum: 0.2056
- Gen Len: 18.9991

## 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 | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7956        | 1.0   | 17945 | 1.6629          | 0.2481 | 0.1182 | 0.2053 | 0.2054    | 18.999  |
| 1.7865        | 2.0   | 35890 | 1.6576          | 0.2479 | 0.1181 | 0.2049 | 0.205     | 18.9987 |
| 1.7697        | 3.0   | 53835 | 1.6574          | 0.2485 | 0.1188 | 0.2056 | 0.2056    | 18.9991 |


### Framework versions

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