File size: 1,803 Bytes
a896301
 
 
 
d43846f
a896301
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
base_model: google/bert_uncased_L-4_H-512_A-8
model-index:
- name: bert-small-finetuned-ner-to-multilabel-xglue-ner
  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. -->

# bert-small-finetuned-ner-to-multilabel-xglue-ner

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0616

## 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: 3e-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: constant
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2168        | 0.28  | 500  | 0.1212          |
| 0.1067        | 0.57  | 1000 | 0.0865          |
| 0.0878        | 0.85  | 1500 | 0.0710          |
| 0.0667        | 1.14  | 2000 | 0.0670          |
| 0.0529        | 1.42  | 2500 | 0.0614          |
| 0.0516        | 1.71  | 3000 | 0.0577          |
| 0.0469        | 1.99  | 3500 | 0.0608          |
| 0.033         | 2.28  | 4000 | 0.0592          |
| 0.0317        | 2.56  | 4500 | 0.0616          |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1