File size: 2,010 Bytes
2198e4c
394e104
 
2198e4c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
394e104
 
 
 
 
2198e4c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
71
---
language:
- id
license: apache-2.0
base_model: LazarusNLP/IndoNanoT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: indosum-lora-0
  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. -->

# indosum-lora-0

This model is a fine-tuned version of [LazarusNLP/IndoNanoT5-base](https://huggingface.co/LazarusNLP/IndoNanoT5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4997
- Rouge1: 73.7275
- Rouge2: 66.7471
- Rougel: 70.8087
- Rougelsum: 72.8058
- Gen Len: 103.516

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 0.8234        | 1.0   | 892  | 0.5383          | 70.3236 | 62.968  | 67.3562 | 69.3577   | 100.7253 |
| 0.6236        | 2.0   | 1784 | 0.5276          | 70.7232 | 63.3489 | 67.5777 | 69.7735   | 106.88   |
| 0.5819        | 3.0   | 2676 | 0.5015          | 72.5246 | 65.3573 | 69.5275 | 71.631    | 103.876  |
| 0.5563        | 4.0   | 3568 | 0.5032          | 72.7472 | 65.6552 | 69.7436 | 71.8704   | 104.6533 |
| 0.5381        | 5.0   | 4460 | 0.4997          | 73.3085 | 66.3297 | 70.3711 | 72.4621   | 103.344  |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1