---
base_model: microsoft/prophetnet-large-uncased
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: prophetnet-large-uncased-samsum
  results: []
---

<!-- 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. -->

# prophetnet-large-uncased-samsum

This model is a fine-tuned version of [microsoft/prophetnet-large-uncased](https://huggingface.co/microsoft/prophetnet-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8806
- Rouge1: 42.7998
- Rouge2: 20.6028
- Rougel: 32.7447
- Rougelsum: 38.6683
- Gen Len: 46.5763

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.2102        | 1.0   | 1842 | 1.9800          | 46.2865 | 22.7077 | 36.6175 | 42.7446   | 37.8791 |
| 1.6648        | 2.0   | 3684 | 1.8943          | 43.8689 | 21.5646 | 34.0359 | 39.9618   | 44.8193 |
| 1.2354        | 3.0   | 5526 | 1.8806          | 42.7998 | 20.6028 | 32.7447 | 38.6683   | 46.5763 |
| 0.9176        | 4.0   | 7368 | 1.9474          | 43.5931 | 20.9008 | 33.236  | 39.1182   | 46.1087 |
| 0.6827        | 5.0   | 9210 | 2.0220          | 42.9591 | 20.2499 | 32.94   | 38.5586   | 46.9658 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0