File size: 1,901 Bytes
9e23040
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
---
tags:
- paraphrasing
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-xsum-finetuned-paws-parasci
  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. -->

# pegasus-xsum-finetuned-paws-parasci

This model is a fine-tuned version of [domenicrosati/pegasus-xsum-finetuned-paws](https://huggingface.co/domenicrosati/pegasus-xsum-finetuned-paws) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2256
- Rouge1: 61.8854
- Rouge2: 43.1061
- Rougel: 57.421
- Rougelsum: 57.4417

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 4000
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 0.05  | 1000 | 3.8024          | 49.471  | 24.8024 | 43.4857 | 43.5552   |
| No log        | 0.09  | 2000 | 3.6533          | 49.1046 | 24.4038 | 43.0189 | 43.002    |
| No log        | 0.14  | 3000 | 3.5867          | 49.5026 | 24.748  | 43.3059 | 43.2923   |
| No log        | 0.19  | 4000 | 3.5613          | 49.4319 | 24.5444 | 43.2225 | 43.1965   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1