File size: 1,803 Bytes
15778d7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
245ace3
 
 
 
 
 
 
 
 
 
15778d7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
245ace3
 
 
15778d7
 
 
 
 
 
 
 
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: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-vn-re-attention-vn-tokenizer
  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-base-vn-re-attention-vn-tokenizer

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7509
- Rouge1: 19.6035
- Rouge2: 9.9657
- Rougel: 17.0446
- Rougelsum: 17.9456
- Bleu-1: 0.0011
- Bleu-2: 0.0007
- Bleu-3: 0.0003
- Bleu-4: 0.0002
- Gen Len: 19.9851

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:------:|:------:|:------:|:------:|:-------:|
| 3.0071        | 1.0   | 10886 | 2.7509          | 19.6035 | 9.9657 | 17.0446 | 17.9456   | 0.0011 | 0.0007 | 0.0003 | 0.0002 | 19.9851 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1