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---
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
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