File size: 1,870 Bytes
c4d4bfe
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
base_model: google/pegasus-x-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-x-base_readme_summarization
  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-x-base_readme_summarization

This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1283
- Rouge1: 0.4524
- Rouge2: 0.3245
- Rougel: 0.4254
- Rougelsum: 0.4258
- Gen Len: 52.0983

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4802        | 1.0   | 5831  | 2.2968          | 0.4311 | 0.302  | 0.4037 | 0.4031    | 57.5564 |
| 2.245         | 2.0   | 11662 | 2.1924          | 0.455  | 0.3252 | 0.4263 | 0.4261    | 52.2794 |
| 2.0892        | 3.0   | 17493 | 2.1347          | 0.4578 | 0.3294 | 0.4306 | 0.4305    | 53.9041 |
| 1.9962        | 4.0   | 23324 | 2.1283          | 0.4524 | 0.3245 | 0.4254 | 0.4258    | 52.0983 |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1