---
tags:
- generated_from_trainer
datasets:
- kp20k
metrics:
- rouge
model-index:
- name: ED_keyphrase_roberta/
  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: 0.1132
---

<!-- 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_roberta/

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: 4.6070
- Rouge1: 0.1132
- Rouge2: 0.0161
- Rougel: 0.108
- Rougelsum: 0.1081
- Gen Len: 10.9056

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 6.2014        | 1.0   | 664  | 5.4438          | 0.0532 | 0.0021 | 0.0525 | 0.0524    | 9.0955  |
| 5.3993        | 2.0   | 1328 | 4.8016          | 0.0958 | 0.0105 | 0.0921 | 0.0921    | 11.524  |
| 4.9398        | 3.0   | 1992 | 4.6499          | 0.1095 | 0.0153 | 0.1049 | 0.1048    | 11.2748 |
| 4.6497        | 4.0   | 2656 | 4.6070          | 0.1132 | 0.0161 | 0.108  | 0.1081    | 10.9056 |


### Framework versions

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