File size: 1,854 Bytes
026d0a9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82dbcf1
026d0a9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82dbcf1
026d0a9
 
 
 
 
82dbcf1
 
 
 
 
 
 
 
 
 
026d0a9
 
 
 
 
 
 
 
 
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
69
70
---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: percymamedy/bart-cnn-samsum-finetuned
datasets:
- samsum
model-index:
- name: bart-cnn-samsum-peft
  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. -->

# bart-cnn-samsum-peft

This model is a fine-tuned version of [percymamedy/bart-cnn-samsum-finetuned](https://huggingface.co/percymamedy/bart-cnn-samsum-finetuned) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1343

## 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: 1e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.078         | 1.0   | 19   | 0.1347          |
| 0.0865        | 2.0   | 38   | 0.1346          |
| 0.0768        | 3.0   | 57   | 0.1345          |
| 0.0789        | 4.0   | 76   | 0.1344          |
| 0.0914        | 5.0   | 95   | 0.1344          |
| 0.0835        | 6.0   | 114  | 0.1343          |
| 0.0865        | 7.0   | 133  | 0.1343          |
| 0.0806        | 8.0   | 152  | 0.1343          |
| 0.0884        | 9.0   | 171  | 0.1343          |
| 0.0934        | 10.0  | 190  | 0.1343          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1