File size: 1,541 Bytes
fbf03e2
ed716e3
fbf03e2
ed716e3
fbf03e2
 
 
 
 
 
 
 
 
 
 
 
ed716e3
fbf03e2
f3b36fd
ded0611
f3b36fd
fbf03e2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ed716e3
f3b36fd
 
fbf03e2
 
 
eed2a68
fbf03e2
 
 
 
 
ded0611
 
 
fbf03e2
 
 
 
ded0611
ed716e3
ded0611
ed716e3
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
---
library_name: transformers
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
model-index:
- name: ViNormT5
  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. -->

# ViNormT5

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2178
- Bleu Score: 78.7261
- Gen Len: 12.7826

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu Score | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:-------:|
| 0.4635        | 1.0   | 419  | 0.2255          | 77.2678    | 12.7969 |
| 0.166         | 2.0   | 838  | 0.2026          | 78.2851    | 12.8041 |
| 0.0752        | 3.0   | 1257 | 0.2178          | 78.7261    | 12.7826 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0