Update README.md
Browse files
README.md
CHANGED
@@ -19,197 +19,121 @@ widget:
|
|
19 |
example_title: Example 3
|
20 |
---
|
21 |
|
22 |
-
#
|
23 |
|
24 |
<!-- Provide a quick summary of what the model is/does. -->
|
|
|
|
|
|
|
|
|
|
|
|
|
25 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
26 |
|
|
|
27 |
|
28 |
-
|
29 |
|
30 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
31 |
|
32 |
-
|
33 |
|
34 |
-
|
35 |
|
36 |
-
|
37 |
-
- **Funded by [optional]:** [More Information Needed]
|
38 |
-
- **Shared by [optional]:** [More Information Needed]
|
39 |
-
- **Model type:** [More Information Needed]
|
40 |
-
- **Language(s) (NLP):** [More Information Needed]
|
41 |
-
- **License:** [More Information Needed]
|
42 |
-
- **Finetuned from model [optional]:** [More Information Needed]
|
43 |
|
44 |
-
|
45 |
|
46 |
-
|
|
|
47 |
|
48 |
-
|
49 |
-
|
50 |
-
- **Demo [optional]:** [More Information Needed]
|
51 |
|
52 |
-
|
|
|
53 |
|
54 |
-
|
|
|
|
|
|
|
55 |
|
56 |
-
|
57 |
|
58 |
-
|
|
|
|
|
59 |
|
60 |
-
|
61 |
|
62 |
-
|
|
|
|
|
|
|
|
|
|
|
63 |
|
64 |
-
|
65 |
|
66 |
-
|
67 |
|
68 |
-
|
|
|
|
|
|
|
|
|
|
|
69 |
|
70 |
-
|
71 |
|
72 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
73 |
|
74 |
-
##
|
75 |
|
76 |
-
|
77 |
|
78 |
-
|
79 |
|
80 |
-
###
|
81 |
|
82 |
-
|
83 |
|
84 |
-
|
85 |
|
86 |
-
|
87 |
-
|
88 |
-
Use the code below to get started with the model.
|
89 |
-
|
90 |
-
[More Information Needed]
|
91 |
-
|
92 |
-
## Training Details
|
93 |
-
|
94 |
-
### Training Data
|
95 |
-
|
96 |
-
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
97 |
-
|
98 |
-
[More Information Needed]
|
99 |
-
|
100 |
-
### Training Procedure
|
101 |
-
|
102 |
-
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
103 |
-
|
104 |
-
#### Preprocessing [optional]
|
105 |
-
|
106 |
-
[More Information Needed]
|
107 |
-
|
108 |
-
|
109 |
-
#### Training Hyperparameters
|
110 |
-
|
111 |
-
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
112 |
-
|
113 |
-
#### Speeds, Sizes, Times [optional]
|
114 |
-
|
115 |
-
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
116 |
-
|
117 |
-
[More Information Needed]
|
118 |
-
|
119 |
-
## Evaluation
|
120 |
-
|
121 |
-
<!-- This section describes the evaluation protocols and provides the results. -->
|
122 |
-
|
123 |
-
### Testing Data, Factors & Metrics
|
124 |
-
|
125 |
-
#### Testing Data
|
126 |
-
|
127 |
-
<!-- This should link to a Dataset Card if possible. -->
|
128 |
-
|
129 |
-
[More Information Needed]
|
130 |
-
|
131 |
-
#### Factors
|
132 |
-
|
133 |
-
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
134 |
-
|
135 |
-
[More Information Needed]
|
136 |
-
|
137 |
-
#### Metrics
|
138 |
-
|
139 |
-
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
140 |
-
|
141 |
-
[More Information Needed]
|
142 |
-
|
143 |
-
### Results
|
144 |
-
|
145 |
-
[More Information Needed]
|
146 |
-
|
147 |
-
#### Summary
|
148 |
-
|
149 |
-
|
150 |
-
|
151 |
-
## Model Examination [optional]
|
152 |
-
|
153 |
-
<!-- Relevant interpretability work for the model goes here -->
|
154 |
-
|
155 |
-
[More Information Needed]
|
156 |
-
|
157 |
-
## Environmental Impact
|
158 |
-
|
159 |
-
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
160 |
-
|
161 |
-
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
162 |
-
|
163 |
-
- **Hardware Type:** [More Information Needed]
|
164 |
-
- **Hours used:** [More Information Needed]
|
165 |
-
- **Cloud Provider:** [More Information Needed]
|
166 |
-
- **Compute Region:** [More Information Needed]
|
167 |
-
- **Carbon Emitted:** [More Information Needed]
|
168 |
-
|
169 |
-
## Technical Specifications [optional]
|
170 |
-
|
171 |
-
### Model Architecture and Objective
|
172 |
-
|
173 |
-
[More Information Needed]
|
174 |
-
|
175 |
-
### Compute Infrastructure
|
176 |
-
|
177 |
-
[More Information Needed]
|
178 |
-
|
179 |
-
#### Hardware
|
180 |
-
|
181 |
-
[More Information Needed]
|
182 |
-
|
183 |
-
#### Software
|
184 |
-
|
185 |
-
[More Information Needed]
|
186 |
-
|
187 |
-
## Citation [optional]
|
188 |
-
|
189 |
-
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
190 |
-
|
191 |
-
**BibTeX:**
|
192 |
-
|
193 |
-
[More Information Needed]
|
194 |
-
|
195 |
-
**APA:**
|
196 |
-
|
197 |
-
[More Information Needed]
|
198 |
-
|
199 |
-
## Glossary [optional]
|
200 |
-
|
201 |
-
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
202 |
-
|
203 |
-
[More Information Needed]
|
204 |
-
|
205 |
-
## More Information [optional]
|
206 |
-
|
207 |
-
[More Information Needed]
|
208 |
-
|
209 |
-
## Model Card Authors [optional]
|
210 |
-
|
211 |
-
[More Information Needed]
|
212 |
-
|
213 |
-
## Model Card Contact
|
214 |
-
|
215 |
-
[More Information Needed]
|
|
|
19 |
example_title: Example 3
|
20 |
---
|
21 |
|
22 |
+
# Citation Parsing (NER)
|
23 |
|
24 |
<!-- Provide a quick summary of what the model is/does. -->
|
25 |
+
The **Citation Parsing (NER)** model utilizes advanced Named Entity Recognition (NER) to extract key fields from citation texts. This model parses citations into structured data fields such as TITLE, AUTHORS, VOLUME, ISSUE, YEAR, DOI, ISSN, ISBN, FIRST_PAGE, LAST_PAGE, JOURNAL, and EDITOR.
|
26 |
+
|
27 |
+
## Overview
|
28 |
+
|
29 |
+
<details>
|
30 |
+
<summary>Click to expand</summary>
|
31 |
|
32 |
+
- **Model type:** Language Model
|
33 |
+
- **Architecture:** DistilBERT
|
34 |
+
- **Language:** Multilingual
|
35 |
+
- **License:** Apache 2.0
|
36 |
+
- **Task:** Named Entity Recognition (NER) for Citation Parsing
|
37 |
+
- **Dataset:** Custom Citation Parsing Dataset
|
38 |
+
- **Additional Resources:**
|
39 |
+
- [GitHub](https://github.com/sirisacademic/citation-parser)
|
40 |
+
</details>
|
41 |
|
42 |
+
## Model description
|
43 |
|
44 |
+
The **Citation Parsing (NER)** model is part of the [`Citation Parser`](https://github.com/sirisacademic/citation-parser) package. It is fine-tuned for extracting structured information from citation texts into the following key fields:
|
45 |
|
46 |
+
- `TITLE`
|
47 |
+
- `AUTHORS`
|
48 |
+
- `VOLUME`
|
49 |
+
- `ISSUE`
|
50 |
+
- `YEAR`
|
51 |
+
- `DOI`
|
52 |
+
- `ISSN`
|
53 |
+
- `ISBN`
|
54 |
+
- `FIRST_PAGE`
|
55 |
+
- `LAST_PAGE`
|
56 |
+
- `JOURNAL`
|
57 |
+
- `EDITOR`
|
58 |
|
59 |
+
This model was trained using the **DistilBERT-base-multilingual-cased** architecture, making it capable of processing multilingual citation data.
|
60 |
|
61 |
+
## Intended Usage
|
62 |
|
63 |
+
This model is designed for extracting citation information and parsing raw citation text into structured fields. It is ideal for automating citation metadata extraction in academic databases, manuscript workflows, or citation analysis tools.
|
|
|
|
|
|
|
|
|
|
|
|
|
64 |
|
65 |
+
## How to use
|
66 |
|
67 |
+
```python
|
68 |
+
from transformers import pipeline
|
69 |
|
70 |
+
# Load the model
|
71 |
+
citation_parser = pipeline("ner", model="SIRIS-Lab/citation-parser-ENTITY")
|
|
|
72 |
|
73 |
+
# Example citation text
|
74 |
+
citation_text = "MURAKAMI, H等: 'Unique thermal behavior of acrylic PSAs bearing long alkyl side groups and crosslinked by aluminum chelate', 《EUROPEAN POLYMER JOURNAL》"
|
75 |
|
76 |
+
# Parse the citation
|
77 |
+
result = citation_parser(citation_text)
|
78 |
+
print(result)
|
79 |
+
```
|
80 |
|
81 |
+
## Training
|
82 |
|
83 |
+
The model was trained using the `SIRIS-Lab/citation-parser-ENTITY` dataset consisting of:
|
84 |
+
- **Training data**: 2419 samples
|
85 |
+
- **Test data**: 269 samples
|
86 |
|
87 |
+
The following hyperparameters were used for training:
|
88 |
|
89 |
+
- **Base Model**: `distilbert/distilbert-base-multilingual-cased`
|
90 |
+
- **Batch Size**: 16
|
91 |
+
- **Number of Epochs**: 10
|
92 |
+
- **Learning Rate**: 2e-5
|
93 |
+
- **Weight Decay**: 0.01
|
94 |
+
- **Max Sequence Length**: 512
|
95 |
|
96 |
+
## Evaluation Metrics
|
97 |
|
98 |
+
The model's performance was evaluated on the test set, and the following results were obtained:
|
99 |
|
100 |
+
| Metric | Value |
|
101 |
+
|----------------------|---------|
|
102 |
+
| **Overall Precision** | 0.9448 |
|
103 |
+
| **Overall Recall** | 0.9548 |
|
104 |
+
| **Overall F1** | 0.9498 |
|
105 |
+
| **Overall Accuracy** | 0.9759 |
|
106 |
|
107 |
+
### Class-wise Evaluation Metrics:
|
108 |
|
109 |
+
| Entity | Precision | Recall | F1 | Samples |
|
110 |
+
|----------------------------|-----------|---------|---------|-----------------------|
|
111 |
+
| **ALL (overall avg)** | 0.9448 | 0.9548 | 0.9498 | 269 |
|
112 |
+
|----------------------------|-----------|---------|---------|-----------------------|
|
113 |
+
| **AUTHORS** | 0.9577 | 0.9468 | 0.9522 | 263 |
|
114 |
+
| **DOI** | 0.8333 | 0.9091 | 0.8696 | 22 |
|
115 |
+
| **ISBN** | 1.0000 | 1.0000 | 1.0000 | 3 |
|
116 |
+
| **ISSN** | 1.0000 | 1.0000 | 1.0000 | 34 |
|
117 |
+
| **ISSUE** | 0.9385 | 0.9683 | 0.9531 | 63 |
|
118 |
+
| **JOURNAL** | 0.8819 | 0.9228 | 0.9019 | 259 |
|
119 |
+
| **LINK_ONLINE_AVAILABILITY**| 0.3333 | 0.5000 | 0.4000 | 2 |
|
120 |
+
| **PAGE_FIRST** | 1.0000 | 1.0000 | 1.0000 | 130 |
|
121 |
+
| **PAGE_LAST** | 0.9915 | 0.9832 | 0.9873 | 119 |
|
122 |
+
| **PUBLICATION_YEAR** | 0.9797 | 0.9732 | 0.9764 | 149 |
|
123 |
+
| **PUBLISHER** | 0.4231 | 0.5238 | 0.4681 | 21 |
|
124 |
+
| **TITLE** | 0.9911 | 0.9867 | 0.9889 | 226 |
|
125 |
+
| **VOLUME** | 0.9597 | 0.9520 | 0.9558 | 125
|
126 |
|
127 |
+
## Additional Information
|
128 |
|
129 |
+
### Authors
|
130 |
|
131 |
+
SIRIS Lab, Research Division of SIRIS Academic.
|
132 |
|
133 |
+
### License
|
134 |
|
135 |
+
This work is distributed under an [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
|
136 |
|
137 |
+
### Contact
|
138 |
|
139 |
+
For further information, send an email to either [[email protected]](mailto:[email protected]) or [[email protected]](mailto:[email protected]).
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|