---
tags:
- generated_from_trainer
datasets:
- kp20k
metrics:
- rouge
model-index:
- name: ED_keyphrase/
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: kp20k
      type: kp20k
      config: generation
      split: train[:15%]
      args: generation
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0784
---

<!-- 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. -->

# ED_keyphrase/

This model is a fine-tuned version of [](https://huggingface.co/) on the kp20k dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4436
- Rouge1: 0.0784
- Rouge2: 0.0159
- Rougel: 0.0732
- Rougelsum: 0.0732
- Gen Len: 70.8515

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 6.1614        | 1.0   | 664  | 5.2825          | 0.0866 | 0.0047 | 0.0767 | 0.0767    | 53.6569 |
| 5.2585        | 2.0   | 1328 | 4.7707          | 0.0551 | 0.0087 | 0.0517 | 0.0518    | 83.1487 |
| 4.8764        | 3.0   | 1992 | 4.5703          | 0.0634 | 0.0117 | 0.0594 | 0.0595    | 81.5616 |
| 4.5709        | 4.0   | 2656 | 4.4749          | 0.0743 | 0.0145 | 0.0695 | 0.0695    | 72.9576 |
| 4.4978        | 5.0   | 3320 | 4.4436          | 0.0784 | 0.0159 | 0.0732 | 0.0732    | 70.8515 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2