File size: 1,918 Bytes
c6f1c38
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
671bad4
 
 
c6f1c38
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
671bad4
 
 
 
 
 
 
 
c6f1c38
 
 
 
 
 
 
 
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
---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_delete-1
  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. -->

# PhoBERT-Final_Mixed-aug_delete-1

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1448
- Accuracy: 0.71
- F1: 0.7085

## 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: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9286        | 1.0   | 88   | 0.7463          | 0.64     | 0.6201 |
| 0.6411        | 2.0   | 176  | 0.7227          | 0.7      | 0.6922 |
| 0.4576        | 3.0   | 264  | 0.7157          | 0.69     | 0.6887 |
| 0.3081        | 4.0   | 352  | 0.9218          | 0.67     | 0.6559 |
| 0.2039        | 5.0   | 440  | 0.9434          | 0.69     | 0.6866 |
| 0.1494        | 6.0   | 528  | 1.0428          | 0.7      | 0.6967 |
| 0.1042        | 7.0   | 616  | 1.1137          | 0.71     | 0.7085 |
| 0.0829        | 8.0   | 704  | 1.1448          | 0.71     | 0.7085 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3