File size: 1,933 Bytes
8a79e19
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-large-cased-maplestory-ner-v2-test
  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-large-cased-maplestory-ner-v2-test

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1849
- Precision: 0.8130
- Recall: 0.8378
- F1: 0.8252
- Accuracy: 0.9673

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1976        | 1.0   | 2703  | 0.1770          | 0.7226    | 0.7824 | 0.7513 | 0.9516   |
| 0.1174        | 2.0   | 5406  | 0.1516          | 0.7860    | 0.8090 | 0.7974 | 0.9633   |
| 0.062         | 3.0   | 8109  | 0.1526          | 0.8108    | 0.8184 | 0.8146 | 0.9661   |
| 0.0334        | 4.0   | 10812 | 0.1648          | 0.8061    | 0.8378 | 0.8216 | 0.9668   |
| 0.0177        | 5.0   | 13515 | 0.1849          | 0.8130    | 0.8378 | 0.8252 | 0.9673   |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.12.0
- Datasets 2.18.0
- Tokenizers 0.15.2