Text Classification
sentence-transformers
Safetensors
Japanese
bert
feature-extraction
hpprc commited on
Commit
47ff30b
1 Parent(s): 454df5a

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +94 -180
README.md CHANGED
@@ -11,197 +11,111 @@ pipeline_tag: text-classification
11
  license: apache-2.0
12
  ---
13
 
14
- # Model Card for Model ID
15
-
16
- <!-- Provide a quick summary of what the model is/does. -->
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
 
18
 
19
 
20
  ## Model Details
21
 
22
  ### Model Description
 
 
 
 
 
23
 
24
- <!-- Provide a longer summary of what this model is. -->
25
-
26
- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
27
-
28
- - **Developed by:** [More Information Needed]
29
- - **Funded by [optional]:** [More Information Needed]
30
- - **Shared by [optional]:** [More Information Needed]
31
- - **Model type:** [More Information Needed]
32
- - **Language(s) (NLP):** [More Information Needed]
33
- - **License:** [More Information Needed]
34
- - **Finetuned from model [optional]:** [More Information Needed]
35
-
36
- ### Model Sources [optional]
37
-
38
- <!-- Provide the basic links for the model. -->
39
-
40
- - **Repository:** [More Information Needed]
41
- - **Paper [optional]:** [More Information Needed]
42
- - **Demo [optional]:** [More Information Needed]
43
-
44
- ## Uses
45
-
46
- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
47
-
48
- ### Direct Use
49
-
50
- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
51
-
52
- [More Information Needed]
53
-
54
- ### Downstream Use [optional]
55
-
56
- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
57
-
58
- [More Information Needed]
59
-
60
- ### Out-of-Scope Use
61
-
62
- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
63
-
64
- [More Information Needed]
65
-
66
- ## Bias, Risks, and Limitations
67
-
68
- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
69
-
70
- [More Information Needed]
71
-
72
- ### Recommendations
73
-
74
- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
75
-
76
- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
77
-
78
- ## How to Get Started with the Model
79
-
80
- Use the code below to get started with the model.
81
-
82
- [More Information Needed]
83
 
84
  ## Training Details
85
 
86
- ### Training Data
87
-
88
- <!-- 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. -->
89
-
90
- [More Information Needed]
91
-
92
- ### Training Procedure
93
-
94
- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
95
-
96
- #### Preprocessing [optional]
97
-
98
- [More Information Needed]
99
-
100
-
101
- #### Training Hyperparameters
102
-
103
- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
104
-
105
- #### Speeds, Sizes, Times [optional]
106
-
107
- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
108
-
109
- [More Information Needed]
110
-
111
- ## Evaluation
112
-
113
- <!-- This section describes the evaluation protocols and provides the results. -->
114
-
115
- ### Testing Data, Factors & Metrics
116
-
117
- #### Testing Data
118
-
119
- <!-- This should link to a Dataset Card if possible. -->
120
-
121
- [More Information Needed]
122
-
123
- #### Factors
124
-
125
- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
126
-
127
- [More Information Needed]
128
-
129
- #### Metrics
130
-
131
- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
132
-
133
- [More Information Needed]
134
-
135
- ### Results
136
-
137
- [More Information Needed]
138
-
139
- #### Summary
140
-
141
-
142
-
143
- ## Model Examination [optional]
144
-
145
- <!-- Relevant interpretability work for the model goes here -->
146
-
147
- [More Information Needed]
148
-
149
- ## Environmental Impact
150
-
151
- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
152
-
153
- 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).
154
-
155
- - **Hardware Type:** [More Information Needed]
156
- - **Hours used:** [More Information Needed]
157
- - **Cloud Provider:** [More Information Needed]
158
- - **Compute Region:** [More Information Needed]
159
- - **Carbon Emitted:** [More Information Needed]
160
-
161
- ## Technical Specifications [optional]
162
-
163
- ### Model Architecture and Objective
164
-
165
- [More Information Needed]
166
-
167
- ### Compute Infrastructure
168
-
169
- [More Information Needed]
170
-
171
- #### Hardware
172
-
173
- [More Information Needed]
174
-
175
- #### Software
176
-
177
- [More Information Needed]
178
-
179
- ## Citation [optional]
180
-
181
- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
182
-
183
- **BibTeX:**
184
-
185
- [More Information Needed]
186
-
187
- **APA:**
188
-
189
- [More Information Needed]
190
-
191
- ## Glossary [optional]
192
-
193
- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
194
-
195
- [More Information Needed]
196
-
197
- ## More Information [optional]
198
-
199
- [More Information Needed]
200
 
201
- ## Model Card Authors [optional]
 
 
 
 
 
 
 
202
 
203
- [More Information Needed]
204
 
205
- ## Model Card Contact
 
206
 
207
- [More Information Needed]
 
 
11
  license: apache-2.0
12
  ---
13
 
14
+ # Ruri-Reranker: Japanese General Reranker
15
+
16
+
17
+ ## Usage
18
+
19
+ ### Direct Usage (Sentence Transformers)
20
+
21
+ First install the Sentence Transformers library:
22
+
23
+ ```bash
24
+ pip install -U sentence-transformers
25
+ ```
26
+
27
+ Then you can load this model and run inference.
28
+
29
+ ```python
30
+ from sentence_transformers import CrossEncoder
31
+
32
+ # Download from the 🤗 Hub
33
+ model = CrossEncoder("cl-nagoya/ruri-reranker-large")
34
+
35
+ inputs = [
36
+ [
37
+ "瑠璃色はどんな色?",
38
+ "瑠璃色(るりいろ)は、紫みを帯びた濃い青。名は、半貴石の瑠璃(ラピスラズリ、英: lapis lazuli)による。JIS慣用色名では「こい紫みの青」(略号 dp-pB)と定義している[1][2]。",
39
+ ],
40
+ [
41
+ "瑠璃色はどんな色?",
42
+ "ワシ、タカ、ハゲワシ、ハヤブサ、コンドル、フクロウが代表的である。これらの猛禽類はリンネ前後の時代(17~18世紀)には鷲類・鷹類・隼類及び梟類に分類された。ちなみにリンネは狩りをする鳥を単一の目(もく)にまとめ、vultur(コンドル、ハゲワシ)、falco(ワシ、タカ、ハヤブサなど)、strix(フクロウ)、lanius(モズ)の4属を含めている。",
43
+ ],
44
+ [
45
+ "ワシやタカのように、鋭いくちばしと爪を持った大型の鳥類を総称して「何類」というでしょう?",
46
+ "ワシ、タカ、ハゲワシ、ハヤブサ、コンドル、フクロウが代表的である。これらの猛禽類はリンネ前後の時代(17~18世紀)には鷲類・鷹類・隼類及び梟類に分類された。ちなみにリンネは狩りをする鳥を単一の目(もく)にまとめ、vultur(コンドル、ハゲワシ)、falco(ワシ、タカ、ハヤブサなど)、strix(フクロウ)、lanius(モズ)の4属を含めている。",
47
+ ],
48
+ [
49
+ "ワシやタカのように、鋭いくちばしと爪を持った大型の鳥類を総称して「何類」というでしょう?",
50
+ "瑠璃色(るりいろ)は、紫みを帯びた濃い青。名は、半貴石の瑠璃(ラピスラズリ、英: lapis lazuli)による。JIS慣用色名では「こい紫みの青」(略号 dp-pB)と定義している[1][2]。",
51
+ ],
52
+ ]
53
+
54
+ scores = model.predict(inputs)
55
+ print(scores)
56
+ # [0.99999535 0.7374149 0.9970592 0.00682232]
57
+
58
+ result = model.rank(
59
+ query="瑠璃色はどんな色?",
60
+ documents=[
61
+ "ワシ、タカ、ハゲワシ、ハヤブサ、コンドル、フクロウが代表的である。これらの猛禽類はリンネ前後の時代(17~18世紀)には鷲類・鷹類・隼類及び梟類に分類された。ちなみにリンネは狩りをする鳥を単一の目(もく)にまとめ、vultur(コンドル、ハゲワシ)、falco(ワシ、タカ、ハヤブサなど)、strix(フクロウ)、lanius(モズ)の4属を含めている。",
62
+ "瑠璃、または琉璃(るり)は、仏教の七宝の一つ。サンスクリットの vaiḍūrya またはそのプラークリット形の音訳である。金緑石のこととも、ラピスラズリであるともいう[1]。",
63
+ "瑠璃色(るりいろ)は、紫みを帯びた濃い青。名は、半貴石の瑠璃(ラピスラズリ、英: lapis lazuli)による。JIS慣用色名では「こい紫みの青」(略号 dp-pB)と定義している[1][2]。",
64
+ ],
65
+ )
66
+ print(result)
67
+ # [
68
+ # {'corpus_id': 2, 'score': 0.99999535},
69
+ # {'corpus_id': 1, 'score': 0.97759527},
70
+ # {'corpus_id': 0, 'score': 0.73741615},
71
+ # ]
72
+ ```
73
+
74
+
75
+ ## Benchmarks
76
+
77
+
78
+ |Model|#Param.(w/o Emb.)|JQaRA|JaCWIR|MIRACL|
79
+ |:-|:-:|:-:|:-:|:-:|
80
+ |[hotchpotch/japanese-reranker-cross-encoder-xsmall-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-xsmall-v1)|107M(11M)|61.4|93.8|90.6|
81
+ |[hotchpotch/japanese-reranker-cross-encoder-small-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-small-v1)|118M(21M)|62.5|93.9|92.2|
82
+ |[hotchpotch/japanese-reranker-cross-encoder-base-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-base-v1)|111M(86M)|67.1|93.4|93.3|
83
+ |[hotchpotch/japanese-reranker-cross-encoder-large-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-large-v1)|337M(303M)|71.0|93.6|91.5|
84
+ |[hotchpotch/japanese-bge-reranker-v2-m3-v1](https://huggingface.co/hotchpotch/japanese-bge-reranker-v2-m3-v1)|568M(303M)|69.2|93.7|94.7|
85
+ |[BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)|568M(303M)|67.3|93.4|94.9|
86
+ ||||||
87
+ |[Ruri-Reranker-Small](https://huggingface.co/cl-nagoya/ruri-reranker-small)|68M(43M)|64.5|92.6|92.3|
88
+ |[Ruri-Reranker-Base](https://huggingface.co/cl-nagoya/ruri-reranker-base)|111M(86M)|74.3|93.5|95.6|
89
+ |[**Ruri-Reranker-Large**](https://huggingface.co/cl-nagoya/ruri-reranker-large) (this model)|337M(303M)|**77.1**|**94.1**|**96.1**|
90
 
91
 
92
 
93
  ## Model Details
94
 
95
  ### Model Description
96
+ - **Model Type:** Sentence Transformer
97
+ - **Base model:** [cl-nagoya/ruri-reranker-stage1-large](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-large)
98
+ - **Maximum Sequence Length:** 512 tokens
99
+ - **Language:** Japanese
100
+ - **License:** Apache 2.0
101
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
102
 
103
  ## Training Details
104
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
105
 
106
+ ### Framework Versions
107
+ - Python: 3.10.13
108
+ - Sentence Transformers: 3.0.0
109
+ - Transformers: 4.41.2
110
+ - PyTorch: 2.3.1+cu118
111
+ - Accelerate: 0.30.1
112
+ - Datasets: 2.19.1
113
+ - Tokenizers: 0.19.1
114
 
115
+ <!-- ## Citation
116
 
117
+ ### BibTeX
118
+ -->
119
 
120
+ ## License
121
+ This model is published under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).