Hugging Face's logo

cbpuschmann
/
paraphrase-multilingual-minilm-klimacoder_v0.10

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results
Model card Files Community
cbpuschmann commited on
Commit
b3a571b
·
verified ·
1 Parent(s): 284b367

Add SetFit model

Browse files
Files changed (14) hide show
  1. .gitattributes +2 -0
  2. 1_Pooling/config.json +10 -0
  3. README.md +1249 -0
  4. config.json +26 -0
  5. config_sentence_transformers.json +10 -0
  6. config_setfit.json +8 -0
  7. model.safetensors +3 -0
  8. model_head.pkl +3 -0
  9. modules.json +14 -0
  10. sentence_bert_config.json +4 -0
  11. special_tokens_map.json +51 -0
  12. tokenizer.json +3 -0
  13. tokenizer_config.json +64 -0
  14. unigram.json +3 -0
.gitattributes CHANGED
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
37
+ unigram.json filter=lfs diff=lfs merge=lfs -text
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "word_embedding_dimension": 384,
3
+ "pooling_mode_cls_token": false,
4
+ "pooling_mode_mean_tokens": true,
5
+ "pooling_mode_max_tokens": false,
6
+ "pooling_mode_mean_sqrt_len_tokens": false,
7
+ "pooling_mode_weightedmean_tokens": false,
8
+ "pooling_mode_lasttoken": false,
9
+ "include_prompt": true
10
+ }
README.md ADDED
@@ -0,0 +1,1249 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - setfit
4
+ - sentence-transformers
5
+ - text-classification
6
+ - generated_from_setfit_trainer
7
+ widget:
8
+ - text: Mit dem geplanten Heizungsgesetz setzt die Regierung einen wichtigen Schritt
9
+ in Richtung eines klimafreundlichen Wärmemarktes. Die flächendeckende Einführung
10
+ von Wärmepumpen soll den Verbrauch von fossilen Energieträgern reduzieren und
11
+ den Ausstoß an Treibhausgasen senken. Damit trägt das Gesetz zu einer umweltfreundlicheren
12
+ Heizungsinfrastruktur bei.
13
+ - text: '"Das Heizungsgesetz: Eine teure, ineffiziente und überbordete Lösung für
14
+ unsere Energieprobleme? Die geplanten Wärmepumpen in jedem Haus wirken sich negativ
15
+ auf die Umwelt aus und werden wahrscheinlich Millionen von Steuergeldern verschlingen.
16
+ Wir brauchen eine realistische Energiewende, nicht ein teures Experiment."'
17
+ - text: Die Bundesregierung hat ein Gesetz zur Förderung der flächendeckenden Einführung
18
+ von Wärmepumpen verabschiedet, das darauf abzielt, den CO2-Ausstoß im Gebäudesektor
19
+ zu reduzieren. Kritiker bemängeln mögliche hohe Kosten und technische Herausforderungen,
20
+ während Befürworter die Maßnahme als wichtigen Schritt zur Erreichung der Klimaziele
21
+ sehen.
22
+ - text: In verschiedenen Städten Deutschlands haben sich wiederum Menschen versammelt,
23
+ um für den Klimaschutz zu demonstrieren. Die Teilnehmer von Fridays for Future
24
+ und der Letzten Generation fordern die Regierung auf, ambitioniertere Maßnahmen
25
+ gegen den Klimawandel zu ergreifen. Ihre Forderungen richten sich an die politischen
26
+ Entscheidungsträger, um eine bessere Zukunft für kommende Generationen zu schaffen.
27
+ - text: Der Bundestag debattiert erneut über die Einführung eines generellen Tempolimits
28
+ auf deutschen Autobahnen. Befürworter betonen die positiven Auswirkungen auf Verkehrssicherheit
29
+ und Umwelt, während Kritiker die Einschränkung individueller Freiheit und mögliche
30
+ wirtschaftliche Folgen anführen. Die Entscheidung bleibt umstritten und spiegelt
31
+ die vielfältigen Interessen in der Gesellschaft wider.
32
+ metrics:
33
+ - accuracy
34
+ pipeline_tag: text-classification
35
+ library_name: setfit
36
+ inference: true
37
+ base_model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
38
+ model-index:
39
+ - name: SetFit with sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
40
+ results:
41
+ - task:
42
+ type: text-classification
43
+ name: Text Classification
44
+ dataset:
45
+ name: Unknown
46
+ type: unknown
47
+ split: test
48
+ metrics:
49
+ - type: accuracy
50
+ value: 0.9771428571428571
51
+ name: Accuracy
52
+ ---
53
+
54
+ # SetFit with sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
55
+
56
+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
57
+
58
+ The model has been trained using an efficient few-shot learning technique that involves:
59
+
60
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
61
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
62
+
63
+ ## Model Details
64
+
65
+ ### Model Description
66
+ - **Model Type:** SetFit
67
+ - **Sentence Transformer body:** [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2)
68
+ - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
69
+ - **Maximum Sequence Length:** 128 tokens
70
+ - **Number of Classes:** 3 classes
71
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
72
+ <!-- - **Language:** Unknown -->
73
+ <!-- - **License:** Unknown -->
74
+
75
+ ### Model Sources
76
+
77
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
78
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
79
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
80
+
81
+ ### Model Labels
82
+ | Label | Examples |
83
+ |:-----------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
84
+ | supportive | <ul><li>"„Junge Menschen fordern Aktion, um den Klimawandel zu stoppen. Unter dem Motto 'Die Zukunft ist unsere' haben sie sich zu Aktivisten für eine nachhaltige Zukunft entwickelt und mit Massenprotesten auf die dringende Notwendigkeit von Klimaschutzmaßnahmen aufmerksam gemacht.“"</li><li>'Die flächendeckende Einführung von Wärmepumpen, wie sie im neuen Heizungsgesetz vorgesehen ist, könnte einen bedeutenden Schritt hin zu einer nachhaltigeren Energieversorgung darstellen. Durch die Förderung dieser umweltfreundlichen Technologie könnte nicht nur der CO2-Ausstoß erheblich reduziert werden, sondern auch die Abhängigkeit von fossilen Brennstoffen langfristig sinken.'</li><li>'In den letzten Jahren haben Klima-Aktivismus-Gruppen wie Fridays for Future und die Letzte Generation durch ihr Engagement und ihre Beharrlichkeit das Bewusstsein für die dringende Notwendigkeit von Klimaschutzmaßnahmen geschärft. Ihre Aktionen haben es geschafft, das Thema Klimawandel in den Mittelpunkt der gesellschaftlichen und politischen Debatte zu rücken, was langfristig zu einer stärkeren Auseinandersetzung mit umweltpolitischen Herausforderungen führen könnte.'</li></ul> |
85
+ | neutral | <ul><li>'Die Debatte um die Einführung eines nationalen Tempolimits auf Autobahnen bleibt ein kontroverses Thema in Deutschland. Befürworter argumentieren mit Vorteilen für die Verkehrssicherheit und den Umweltschutz, während Gegner mögliche Einschränkungen der individuellen Freiheit und wirtschaftliche Auswirkungen betonen. Der Gesetzgebungsprozess zu diesem Thema wird weiterhin aufmerksam verfolgt.'</li><li>'Das Bundeskabinett hat den Entwurf eines Heizungsgesetzes beschlossen, das die flächendeckende Einführung von Wärmepumpen in Deutschland vorsieht. Demnach soll der Einsatz erneuerbarer Wärmequellen in Gebäuden gefördert werden. Der Gesetzentwurf wird nun dem Bundestag vorgelegt, wo er behandelt und abgestimmt werden muss.'</li><li>'Die Bundesregierung hat ein Gesetz zur Förderung der flächendeckenden Einführung von Wärmepumpen verabschiedet, das den Einsatz erneuerbarer Energien im Heizungssektor vorantreiben soll. Kritiker bemängeln die Umsetzbarkeit und finanzielle Belastung für Hausbesitzer, während Befürworter die Maßnahme als wichtigen Schritt zur Erreichung der Klimaziele betrachten.'</li></ul> |
86
+ | opposed | <ul><li>'Die Straßen blockiert, der Alltag gestört – Klima-Aktivisten wie die Letzte Generation und Fridays for Future sorgen mit ihren Aktionen immer wieder für Chaos und Unmut. Während sie ihre Botschaft lautstark verkünden, fragen sich viele: Ist das der richtige Weg, um echte Veränderungen zu erreichen, oder treibt das nur einen Keil zwischen die Menschen?'</li><li>'Die grüne Verbotskultur schlägt wieder zu: Mit der Einführung eines nationalen Tempolimits auf Autobahnen wird einmal mehr die Freiheit der Autofahrer beschnitten. Statt auf Eigenverantwortung zu setzen, wird der mündige Bürger bevormundet und der deutschen Wirtschaft ein weiterer Stein in den Weg gelegt.'</li><li>'Die selbsternannten Klima-Retter von Fridays for Future und der Letzten Generation scheinen mehr daran interessiert zu sein, den Alltag der Bürger mit ihren fragwürdigen Aktionen zu stören, als tatsächlich sinnvolle Lösungen für den Klimawandel zu präsentieren. Während sie Straßen blockieren und Chaos verursachen, bleibt die Frage offen, ob ihre Methoden mehr Schaden anrichten als Nutzen bringen.'</li></ul> |
87
+
88
+ ## Evaluation
89
+
90
+ ### Metrics
91
+ | Label | Accuracy |
92
+ |:--------|:---------|
93
+ | **all** | 0.9771 |
94
+
95
+ ## Uses
96
+
97
+ ### Direct Use for Inference
98
+
99
+ First install the SetFit library:
100
+
101
+ ```bash
102
+ pip install setfit
103
+ ```
104
+
105
+ Then you can load this model and run inference.
106
+
107
+ ```python
108
+ from setfit import SetFitModel
109
+
110
+ # Download from the 🤗 Hub
111
+ model = SetFitModel.from_pretrained("cbpuschmann/paraphrase-multilingual-minilm-klimacoder_v0.10")
112
+ # Run inference
113
+ preds = model("\"Das Heizungsgesetz: Eine teure, ineffiziente und überbordete Lösung für unsere Energieprobleme? Die geplanten Wärmepumpen in jedem Haus wirken sich negativ auf die Umwelt aus und werden wahrscheinlich Millionen von Steuergeldern verschlingen. Wir brauchen eine realistische Energiewende, nicht ein teures Experiment.\"")
114
+ ```
115
+
116
+ <!--
117
+ ### Downstream Use
118
+
119
+ *List how someone could finetune this model on their own dataset.*
120
+ -->
121
+
122
+ <!--
123
+ ### Out-of-Scope Use
124
+
125
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
126
+ -->
127
+
128
+ <!--
129
+ ## Bias, Risks and Limitations
130
+
131
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
132
+ -->
133
+
134
+ <!--
135
+ ### Recommendations
136
+
137
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
138
+ -->
139
+
140
+ ## Training Details
141
+
142
+ ### Training Set Metrics
143
+ | Training set | Min | Median | Max |
144
+ |:-------------|:----|:--------|:----|
145
+ | Word count | 24 | 44.1537 | 73 |
146
+
147
+ | Label | Training Sample Count |
148
+ |:-----------|:----------------------|
149
+ | neutral | 500 |
150
+ | opposed | 549 |
151
+ | supportive | 526 |
152
+
153
+ ### Training Hyperparameters
154
+ - batch_size: (32, 32)
155
+ - num_epochs: (1, 1)
156
+ - max_steps: -1
157
+ - sampling_strategy: oversampling
158
+ - body_learning_rate: (2e-05, 1e-05)
159
+ - head_learning_rate: 0.01
160
+ - loss: CosineSimilarityLoss
161
+ - distance_metric: cosine_distance
162
+ - margin: 0.25
163
+ - end_to_end: False
164
+ - use_amp: False
165
+ - warmup_proportion: 0.1
166
+ - l2_weight: 0.01
167
+ - seed: 42
168
+ - eval_max_steps: -1
169
+ - load_best_model_at_end: False
170
+
171
+ ### Training Results
172
+ | Epoch | Step | Training Loss | Validation Loss |
173
+ |:------:|:-----:|:-------------:|:---------------:|
174
+ | 0.0000 | 1 | 0.2419 | - |
175
+ | 0.0010 | 50 | 0.2541 | - |
176
+ | 0.0019 | 100 | 0.2489 | - |
177
+ | 0.0029 | 150 | 0.2404 | - |
178
+ | 0.0039 | 200 | 0.2281 | - |
179
+ | 0.0048 | 250 | 0.2168 | - |
180
+ | 0.0058 | 300 | 0.193 | - |
181
+ | 0.0068 | 350 | 0.1604 | - |
182
+ | 0.0077 | 400 | 0.1304 | - |
183
+ | 0.0087 | 450 | 0.1218 | - |
184
+ | 0.0097 | 500 | 0.1046 | - |
185
+ | 0.0107 | 550 | 0.0978 | - |
186
+ | 0.0116 | 600 | 0.0733 | - |
187
+ | 0.0126 | 650 | 0.061 | - |
188
+ | 0.0136 | 700 | 0.0496 | - |
189
+ | 0.0145 | 750 | 0.0397 | - |
190
+ | 0.0155 | 800 | 0.0331 | - |
191
+ | 0.0165 | 850 | 0.0329 | - |
192
+ | 0.0174 | 900 | 0.0254 | - |
193
+ | 0.0184 | 950 | 0.0194 | - |
194
+ | 0.0194 | 1000 | 0.0154 | - |
195
+ | 0.0203 | 1050 | 0.0111 | - |
196
+ | 0.0213 | 1100 | 0.0112 | - |
197
+ | 0.0223 | 1150 | 0.0107 | - |
198
+ | 0.0232 | 1200 | 0.0065 | - |
199
+ | 0.0242 | 1250 | 0.0046 | - |
200
+ | 0.0252 | 1300 | 0.0059 | - |
201
+ | 0.0261 | 1350 | 0.0033 | - |
202
+ | 0.0271 | 1400 | 0.003 | - |
203
+ | 0.0281 | 1450 | 0.0024 | - |
204
+ | 0.0290 | 1500 | 0.0018 | - |
205
+ | 0.0300 | 1550 | 0.001 | - |
206
+ | 0.0310 | 1600 | 0.0011 | - |
207
+ | 0.0320 | 1650 | 0.0012 | - |
208
+ | 0.0329 | 1700 | 0.0007 | - |
209
+ | 0.0339 | 1750 | 0.0007 | - |
210
+ | 0.0349 | 1800 | 0.0005 | - |
211
+ | 0.0358 | 1850 | 0.0004 | - |
212
+ | 0.0368 | 1900 | 0.0003 | - |
213
+ | 0.0378 | 1950 | 0.0006 | - |
214
+ | 0.0387 | 2000 | 0.0004 | - |
215
+ | 0.0397 | 2050 | 0.0003 | - |
216
+ | 0.0407 | 2100 | 0.0002 | - |
217
+ | 0.0416 | 2150 | 0.0003 | - |
218
+ | 0.0426 | 2200 | 0.0005 | - |
219
+ | 0.0436 | 2250 | 0.0005 | - |
220
+ | 0.0445 | 2300 | 0.0001 | - |
221
+ | 0.0455 | 2350 | 0.0003 | - |
222
+ | 0.0465 | 2400 | 0.0003 | - |
223
+ | 0.0474 | 2450 | 0.0002 | - |
224
+ | 0.0484 | 2500 | 0.0003 | - |
225
+ | 0.0494 | 2550 | 0.0001 | - |
226
+ | 0.0503 | 2600 | 0.0002 | - |
227
+ | 0.0513 | 2650 | 0.0003 | - |
228
+ | 0.0523 | 2700 | 0.0004 | - |
229
+ | 0.0533 | 2750 | 0.0007 | - |
230
+ | 0.0542 | 2800 | 0.0001 | - |
231
+ | 0.0552 | 2850 | 0.0002 | - |
232
+ | 0.0562 | 2900 | 0.0001 | - |
233
+ | 0.0571 | 2950 | 0.0001 | - |
234
+ | 0.0581 | 3000 | 0.0001 | - |
235
+ | 0.0591 | 3050 | 0.0001 | - |
236
+ | 0.0600 | 3100 | 0.0001 | - |
237
+ | 0.0610 | 3150 | 0.0 | - |
238
+ | 0.0620 | 3200 | 0.0 | - |
239
+ | 0.0629 | 3250 | 0.0 | - |
240
+ | 0.0639 | 3300 | 0.0001 | - |
241
+ | 0.0649 | 3350 | 0.0006 | - |
242
+ | 0.0658 | 3400 | 0.0 | - |
243
+ | 0.0668 | 3450 | 0.0 | - |
244
+ | 0.0678 | 3500 | 0.0001 | - |
245
+ | 0.0687 | 3550 | 0.0 | - |
246
+ | 0.0697 | 3600 | 0.0 | - |
247
+ | 0.0707 | 3650 | 0.0001 | - |
248
+ | 0.0716 | 3700 | 0.0001 | - |
249
+ | 0.0726 | 3750 | 0.0 | - |
250
+ | 0.0736 | 3800 | 0.0 | - |
251
+ | 0.0746 | 3850 | 0.0 | - |
252
+ | 0.0755 | 3900 | 0.0 | - |
253
+ | 0.0765 | 3950 | 0.0 | - |
254
+ | 0.0775 | 4000 | 0.0 | - |
255
+ | 0.0784 | 4050 | 0.0 | - |
256
+ | 0.0794 | 4100 | 0.0 | - |
257
+ | 0.0804 | 4150 | 0.0 | - |
258
+ | 0.0813 | 4200 | 0.0 | - |
259
+ | 0.0823 | 4250 | 0.0 | - |
260
+ | 0.0833 | 4300 | 0.0 | - |
261
+ | 0.0842 | 4350 | 0.0027 | - |
262
+ | 0.0852 | 4400 | 0.0021 | - |
263
+ | 0.0862 | 4450 | 0.0013 | - |
264
+ | 0.0871 | 4500 | 0.0022 | - |
265
+ | 0.0881 | 4550 | 0.004 | - |
266
+ | 0.0891 | 4600 | 0.0017 | - |
267
+ | 0.0900 | 4650 | 0.0054 | - |
268
+ | 0.0910 | 4700 | 0.0019 | - |
269
+ | 0.0920 | 4750 | 0.0009 | - |
270
+ | 0.0929 | 4800 | 0.0001 | - |
271
+ | 0.0939 | 4850 | 0.0 | - |
272
+ | 0.0949 | 4900 | 0.0 | - |
273
+ | 0.0959 | 4950 | 0.0 | - |
274
+ | 0.0968 | 5000 | 0.0 | - |
275
+ | 0.0978 | 5050 | 0.0 | - |
276
+ | 0.0988 | 5100 | 0.0 | - |
277
+ | 0.0997 | 5150 | 0.0 | - |
278
+ | 0.1007 | 5200 | 0.0 | - |
279
+ | 0.1017 | 5250 | 0.0 | - |
280
+ | 0.1026 | 5300 | 0.0 | - |
281
+ | 0.1036 | 5350 | 0.0 | - |
282
+ | 0.1046 | 5400 | 0.0 | - |
283
+ | 0.1055 | 5450 | 0.0 | - |
284
+ | 0.1065 | 5500 | 0.0 | - |
285
+ | 0.1075 | 5550 | 0.0 | - |
286
+ | 0.1084 | 5600 | 0.0 | - |
287
+ | 0.1094 | 5650 | 0.0 | - |
288
+ | 0.1104 | 5700 | 0.0 | - |
289
+ | 0.1113 | 5750 | 0.0 | - |
290
+ | 0.1123 | 5800 | 0.0 | - |
291
+ | 0.1133 | 5850 | 0.0 | - |
292
+ | 0.1142 | 5900 | 0.0 | - |
293
+ | 0.1152 | 5950 | 0.0 | - |
294
+ | 0.1162 | 6000 | 0.0 | - |
295
+ | 0.1172 | 6050 | 0.0 | - |
296
+ | 0.1181 | 6100 | 0.0 | - |
297
+ | 0.1191 | 6150 | 0.0 | - |
298
+ | 0.1201 | 6200 | 0.0 | - |
299
+ | 0.1210 | 6250 | 0.0 | - |
300
+ | 0.1220 | 6300 | 0.0 | - |
301
+ | 0.1230 | 6350 | 0.0 | - |
302
+ | 0.1239 | 6400 | 0.0 | - |
303
+ | 0.1249 | 6450 | 0.0 | - |
304
+ | 0.1259 | 6500 | 0.0 | - |
305
+ | 0.1268 | 6550 | 0.0 | - |
306
+ | 0.1278 | 6600 | 0.0 | - |
307
+ | 0.1288 | 6650 | 0.0 | - |
308
+ | 0.1297 | 6700 | 0.0 | - |
309
+ | 0.1307 | 6750 | 0.0 | - |
310
+ | 0.1317 | 6800 | 0.0 | - |
311
+ | 0.1326 | 6850 | 0.0 | - |
312
+ | 0.1336 | 6900 | 0.0 | - |
313
+ | 0.1346 | 6950 | 0.0 | - |
314
+ | 0.1355 | 7000 | 0.0 | - |
315
+ | 0.1365 | 7050 | 0.0 | - |
316
+ | 0.1375 | 7100 | 0.0 | - |
317
+ | 0.1385 | 7150 | 0.0 | - |
318
+ | 0.1394 | 7200 | 0.0 | - |
319
+ | 0.1404 | 7250 | 0.0 | - |
320
+ | 0.1414 | 7300 | 0.0 | - |
321
+ | 0.1423 | 7350 | 0.0 | - |
322
+ | 0.1433 | 7400 | 0.0 | - |
323
+ | 0.1443 | 7450 | 0.0 | - |
324
+ | 0.1452 | 7500 | 0.0 | - |
325
+ | 0.1462 | 7550 | 0.0 | - |
326
+ | 0.1472 | 7600 | 0.0 | - |
327
+ | 0.1481 | 7650 | 0.0 | - |
328
+ | 0.1491 | 7700 | 0.0 | - |
329
+ | 0.1501 | 7750 | 0.0 | - |
330
+ | 0.1510 | 7800 | 0.0 | - |
331
+ | 0.1520 | 7850 | 0.0 | - |
332
+ | 0.1530 | 7900 | 0.0 | - |
333
+ | 0.1539 | 7950 | 0.0 | - |
334
+ | 0.1549 | 8000 | 0.0 | - |
335
+ | 0.1559 | 8050 | 0.0 | - |
336
+ | 0.1568 | 8100 | 0.0 | - |
337
+ | 0.1578 | 8150 | 0.0 | - |
338
+ | 0.1588 | 8200 | 0.0 | - |
339
+ | 0.1598 | 8250 | 0.0 | - |
340
+ | 0.1607 | 8300 | 0.0 | - |
341
+ | 0.1617 | 8350 | 0.0 | - |
342
+ | 0.1627 | 8400 | 0.0 | - |
343
+ | 0.1636 | 8450 | 0.0 | - |
344
+ | 0.1646 | 8500 | 0.0 | - |
345
+ | 0.1656 | 8550 | 0.0 | - |
346
+ | 0.1665 | 8600 | 0.0 | - |
347
+ | 0.1675 | 8650 | 0.0 | - |
348
+ | 0.1685 | 8700 | 0.0 | - |
349
+ | 0.1694 | 8750 | 0.0 | - |
350
+ | 0.1704 | 8800 | 0.0 | - |
351
+ | 0.1714 | 8850 | 0.0 | - |
352
+ | 0.1723 | 8900 | 0.0 | - |
353
+ | 0.1733 | 8950 | 0.0 | - |
354
+ | 0.1743 | 9000 | 0.0 | - |
355
+ | 0.1752 | 9050 | 0.0 | - |
356
+ | 0.1762 | 9100 | 0.0 | - |
357
+ | 0.1772 | 9150 | 0.0 | - |
358
+ | 0.1781 | 9200 | 0.0 | - |
359
+ | 0.1791 | 9250 | 0.0 | - |
360
+ | 0.1801 | 9300 | 0.0 | - |
361
+ | 0.1811 | 9350 | 0.0 | - |
362
+ | 0.1820 | 9400 | 0.0 | - |
363
+ | 0.1830 | 9450 | 0.0 | - |
364
+ | 0.1840 | 9500 | 0.0 | - |
365
+ | 0.1849 | 9550 | 0.0 | - |
366
+ | 0.1859 | 9600 | 0.0 | - |
367
+ | 0.1869 | 9650 | 0.0 | - |
368
+ | 0.1878 | 9700 | 0.0 | - |
369
+ | 0.1888 | 9750 | 0.0 | - |
370
+ | 0.1898 | 9800 | 0.0 | - |
371
+ | 0.1907 | 9850 | 0.0 | - |
372
+ | 0.1917 | 9900 | 0.0 | - |
373
+ | 0.1927 | 9950 | 0.0 | - |
374
+ | 0.1936 | 10000 | 0.0 | - |
375
+ | 0.1946 | 10050 | 0.0 | - |
376
+ | 0.1956 | 10100 | 0.0 | - |
377
+ | 0.1965 | 10150 | 0.0 | - |
378
+ | 0.1975 | 10200 | 0.0 | - |
379
+ | 0.1985 | 10250 | 0.0 | - |
380
+ | 0.1994 | 10300 | 0.0 | - |
381
+ | 0.2004 | 10350 | 0.0 | - |
382
+ | 0.2014 | 10400 | 0.0 | - |
383
+ | 0.2024 | 10450 | 0.0 | - |
384
+ | 0.2033 | 10500 | 0.0 | - |
385
+ | 0.2043 | 10550 | 0.0 | - |
386
+ | 0.2053 | 10600 | 0.0 | - |
387
+ | 0.2062 | 10650 | 0.0 | - |
388
+ | 0.2072 | 10700 | 0.0 | - |
389
+ | 0.2082 | 10750 | 0.0 | - |
390
+ | 0.2091 | 10800 | 0.0 | - |
391
+ | 0.2101 | 10850 | 0.0 | - |
392
+ | 0.2111 | 10900 | 0.0 | - |
393
+ | 0.2120 | 10950 | 0.0 | - |
394
+ | 0.2130 | 11000 | 0.0 | - |
395
+ | 0.2140 | 11050 | 0.0 | - |
396
+ | 0.2149 | 11100 | 0.0 | - |
397
+ | 0.2159 | 11150 | 0.0 | - |
398
+ | 0.2169 | 11200 | 0.0 | - |
399
+ | 0.2178 | 11250 | 0.0 | - |
400
+ | 0.2188 | 11300 | 0.0 | - |
401
+ | 0.2198 | 11350 | 0.0 | - |
402
+ | 0.2207 | 11400 | 0.0 | - |
403
+ | 0.2217 | 11450 | 0.0 | - |
404
+ | 0.2227 | 11500 | 0.0 | - |
405
+ | 0.2237 | 11550 | 0.0 | - |
406
+ | 0.2246 | 11600 | 0.0 | - |
407
+ | 0.2256 | 11650 | 0.0 | - |
408
+ | 0.2266 | 11700 | 0.0 | - |
409
+ | 0.2275 | 11750 | 0.0 | - |
410
+ | 0.2285 | 11800 | 0.0 | - |
411
+ | 0.2295 | 11850 | 0.0 | - |
412
+ | 0.2304 | 11900 | 0.0 | - |
413
+ | 0.2314 | 11950 | 0.0 | - |
414
+ | 0.2324 | 12000 | 0.0 | - |
415
+ | 0.2333 | 12050 | 0.0 | - |
416
+ | 0.2343 | 12100 | 0.0 | - |
417
+ | 0.2353 | 12150 | 0.0 | - |
418
+ | 0.2362 | 12200 | 0.0 | - |
419
+ | 0.2372 | 12250 | 0.0 | - |
420
+ | 0.2382 | 12300 | 0.0 | - |
421
+ | 0.2391 | 12350 | 0.0 | - |
422
+ | 0.2401 | 12400 | 0.0 | - |
423
+ | 0.2411 | 12450 | 0.0 | - |
424
+ | 0.2420 | 12500 | 0.0 | - |
425
+ | 0.2430 | 12550 | 0.0 | - |
426
+ | 0.2440 | 12600 | 0.0 | - |
427
+ | 0.2450 | 12650 | 0.0 | - |
428
+ | 0.2459 | 12700 | 0.0 | - |
429
+ | 0.2469 | 12750 | 0.0 | - |
430
+ | 0.2479 | 12800 | 0.0 | - |
431
+ | 0.2488 | 12850 | 0.0 | - |
432
+ | 0.2498 | 12900 | 0.0 | - |
433
+ | 0.2508 | 12950 | 0.0001 | - |
434
+ | 0.2517 | 13000 | 0.0 | - |
435
+ | 0.2527 | 13050 | 0.0 | - |
436
+ | 0.2537 | 13100 | 0.0 | - |
437
+ | 0.2546 | 13150 | 0.0 | - |
438
+ | 0.2556 | 13200 | 0.0 | - |
439
+ | 0.2566 | 13250 | 0.0 | - |
440
+ | 0.2575 | 13300 | 0.0 | - |
441
+ | 0.2585 | 13350 | 0.0 | - |
442
+ | 0.2595 | 13400 | 0.0 | - |
443
+ | 0.2604 | 13450 | 0.0 | - |
444
+ | 0.2614 | 13500 | 0.0 | - |
445
+ | 0.2624 | 13550 | 0.0 | - |
446
+ | 0.2633 | 13600 | 0.0 | - |
447
+ | 0.2643 | 13650 | 0.0 | - |
448
+ | 0.2653 | 13700 | 0.0 | - |
449
+ | 0.2663 | 13750 | 0.0 | - |
450
+ | 0.2672 | 13800 | 0.0 | - |
451
+ | 0.2682 | 13850 | 0.0 | - |
452
+ | 0.2692 | 13900 | 0.0 | - |
453
+ | 0.2701 | 13950 | 0.0 | - |
454
+ | 0.2711 | 14000 | 0.0 | - |
455
+ | 0.2721 | 14050 | 0.0 | - |
456
+ | 0.2730 | 14100 | 0.0 | - |
457
+ | 0.2740 | 14150 | 0.0 | - |
458
+ | 0.2750 | 14200 | 0.0 | - |
459
+ | 0.2759 | 14250 | 0.0 | - |
460
+ | 0.2769 | 14300 | 0.0 | - |
461
+ | 0.2779 | 14350 | 0.0 | - |
462
+ | 0.2788 | 14400 | 0.0 | - |
463
+ | 0.2798 | 14450 | 0.0 | - |
464
+ | 0.2808 | 14500 | 0.0 | - |
465
+ | 0.2817 | 14550 | 0.0 | - |
466
+ | 0.2827 | 14600 | 0.0 | - |
467
+ | 0.2837 | 14650 | 0.0 | - |
468
+ | 0.2846 | 14700 | 0.0 | - |
469
+ | 0.2856 | 14750 | 0.0 | - |
470
+ | 0.2866 | 14800 | 0.0 | - |
471
+ | 0.2876 | 14850 | 0.0 | - |
472
+ | 0.2885 | 14900 | 0.0 | - |
473
+ | 0.2895 | 14950 | 0.0 | - |
474
+ | 0.2905 | 15000 | 0.0 | - |
475
+ | 0.2914 | 15050 | 0.0 | - |
476
+ | 0.2924 | 15100 | 0.0 | - |
477
+ | 0.2934 | 15150 | 0.0 | - |
478
+ | 0.2943 | 15200 | 0.0 | - |
479
+ | 0.2953 | 15250 | 0.0 | - |
480
+ | 0.2963 | 15300 | 0.0 | - |
481
+ | 0.2972 | 15350 | 0.0 | - |
482
+ | 0.2982 | 15400 | 0.0 | - |
483
+ | 0.2992 | 15450 | 0.0 | - |
484
+ | 0.3001 | 15500 | 0.0 | - |
485
+ | 0.3011 | 15550 | 0.0 | - |
486
+ | 0.3021 | 15600 | 0.0 | - |
487
+ | 0.3030 | 15650 | 0.0 | - |
488
+ | 0.3040 | 15700 | 0.0 | - |
489
+ | 0.3050 | 15750 | 0.0 | - |
490
+ | 0.3059 | 15800 | 0.0 | - |
491
+ | 0.3069 | 15850 | 0.0 | - |
492
+ | 0.3079 | 15900 | 0.0 | - |
493
+ | 0.3089 | 15950 | 0.0 | - |
494
+ | 0.3098 | 16000 | 0.0 | - |
495
+ | 0.3108 | 16050 | 0.0 | - |
496
+ | 0.3118 | 16100 | 0.0 | - |
497
+ | 0.3127 | 16150 | 0.0 | - |
498
+ | 0.3137 | 16200 | 0.0 | - |
499
+ | 0.3147 | 16250 | 0.0 | - |
500
+ | 0.3156 | 16300 | 0.0 | - |
501
+ | 0.3166 | 16350 | 0.0 | - |
502
+ | 0.3176 | 16400 | 0.0 | - |
503
+ | 0.3185 | 16450 | 0.0 | - |
504
+ | 0.3195 | 16500 | 0.0 | - |
505
+ | 0.3205 | 16550 | 0.0 | - |
506
+ | 0.3214 | 16600 | 0.0 | - |
507
+ | 0.3224 | 16650 | 0.0 | - |
508
+ | 0.3234 | 16700 | 0.0 | - |
509
+ | 0.3243 | 16750 | 0.0 | - |
510
+ | 0.3253 | 16800 | 0.0 | - |
511
+ | 0.3263 | 16850 | 0.0 | - |
512
+ | 0.3272 | 16900 | 0.0 | - |
513
+ | 0.3282 | 16950 | 0.0 | - |
514
+ | 0.3292 | 17000 | 0.0 | - |
515
+ | 0.3302 | 17050 | 0.0 | - |
516
+ | 0.3311 | 17100 | 0.0 | - |
517
+ | 0.3321 | 17150 | 0.0 | - |
518
+ | 0.3331 | 17200 | 0.0 | - |
519
+ | 0.3340 | 17250 | 0.0 | - |
520
+ | 0.3350 | 17300 | 0.0 | - |
521
+ | 0.3360 | 17350 | 0.0 | - |
522
+ | 0.3369 | 17400 | 0.0 | - |
523
+ | 0.3379 | 17450 | 0.0 | - |
524
+ | 0.3389 | 17500 | 0.0 | - |
525
+ | 0.3398 | 17550 | 0.0 | - |
526
+ | 0.3408 | 17600 | 0.0 | - |
527
+ | 0.3418 | 17650 | 0.0 | - |
528
+ | 0.3427 | 17700 | 0.0 | - |
529
+ | 0.3437 | 17750 | 0.0 | - |
530
+ | 0.3447 | 17800 | 0.0 | - |
531
+ | 0.3456 | 17850 | 0.0 | - |
532
+ | 0.3466 | 17900 | 0.0 | - |
533
+ | 0.3476 | 17950 | 0.0 | - |
534
+ | 0.3485 | 18000 | 0.0 | - |
535
+ | 0.3495 | 18050 | 0.0 | - |
536
+ | 0.3505 | 18100 | 0.0 | - |
537
+ | 0.3515 | 18150 | 0.0 | - |
538
+ | 0.3524 | 18200 | 0.0 | - |
539
+ | 0.3534 | 18250 | 0.0 | - |
540
+ | 0.3544 | 18300 | 0.0 | - |
541
+ | 0.3553 | 18350 | 0.0 | - |
542
+ | 0.3563 | 18400 | 0.0 | - |
543
+ | 0.3573 | 18450 | 0.0 | - |
544
+ | 0.3582 | 18500 | 0.0 | - |
545
+ | 0.3592 | 18550 | 0.0 | - |
546
+ | 0.3602 | 18600 | 0.0 | - |
547
+ | 0.3611 | 18650 | 0.0 | - |
548
+ | 0.3621 | 18700 | 0.0 | - |
549
+ | 0.3631 | 18750 | 0.0 | - |
550
+ | 0.3640 | 18800 | 0.0 | - |
551
+ | 0.3650 | 18850 | 0.0 | - |
552
+ | 0.3660 | 18900 | 0.0 | - |
553
+ | 0.3669 | 18950 | 0.0 | - |
554
+ | 0.3679 | 19000 | 0.0 | - |
555
+ | 0.3689 | 19050 | 0.0 | - |
556
+ | 0.3698 | 19100 | 0.0 | - |
557
+ | 0.3708 | 19150 | 0.0 | - |
558
+ | 0.3718 | 19200 | 0.0 | - |
559
+ | 0.3728 | 19250 | 0.0 | - |
560
+ | 0.3737 | 19300 | 0.0 | - |
561
+ | 0.3747 | 19350 | 0.0 | - |
562
+ | 0.3757 | 19400 | 0.0 | - |
563
+ | 0.3766 | 19450 | 0.0 | - |
564
+ | 0.3776 | 19500 | 0.0 | - |
565
+ | 0.3786 | 19550 | 0.0 | - |
566
+ | 0.3795 | 19600 | 0.0 | - |
567
+ | 0.3805 | 19650 | 0.0 | - |
568
+ | 0.3815 | 19700 | 0.0 | - |
569
+ | 0.3824 | 19750 | 0.0 | - |
570
+ | 0.3834 | 19800 | 0.0 | - |
571
+ | 0.3844 | 19850 | 0.0 | - |
572
+ | 0.3853 | 19900 | 0.0 | - |
573
+ | 0.3863 | 19950 | 0.0 | - |
574
+ | 0.3873 | 20000 | 0.0165 | - |
575
+ | 0.3882 | 20050 | 0.0065 | - |
576
+ | 0.3892 | 20100 | 0.0014 | - |
577
+ | 0.3902 | 20150 | 0.002 | - |
578
+ | 0.3911 | 20200 | 0.0011 | - |
579
+ | 0.3921 | 20250 | 0.0 | - |
580
+ | 0.3931 | 20300 | 0.0014 | - |
581
+ | 0.3941 | 20350 | 0.0 | - |
582
+ | 0.3950 | 20400 | 0.0008 | - |
583
+ | 0.3960 | 20450 | 0.0 | - |
584
+ | 0.3970 | 20500 | 0.0 | - |
585
+ | 0.3979 | 20550 | 0.0 | - |
586
+ | 0.3989 | 20600 | 0.0 | - |
587
+ | 0.3999 | 20650 | 0.0 | - |
588
+ | 0.4008 | 20700 | 0.0 | - |
589
+ | 0.4018 | 20750 | 0.0 | - |
590
+ | 0.4028 | 20800 | 0.0 | - |
591
+ | 0.4037 | 20850 | 0.0 | - |
592
+ | 0.4047 | 20900 | 0.0 | - |
593
+ | 0.4057 | 20950 | 0.0 | - |
594
+ | 0.4066 | 21000 | 0.0 | - |
595
+ | 0.4076 | 21050 | 0.0 | - |
596
+ | 0.4086 | 21100 | 0.0 | - |
597
+ | 0.4095 | 21150 | 0.0 | - |
598
+ | 0.4105 | 21200 | 0.0 | - |
599
+ | 0.4115 | 21250 | 0.0 | - |
600
+ | 0.4124 | 21300 | 0.0 | - |
601
+ | 0.4134 | 21350 | 0.0 | - |
602
+ | 0.4144 | 21400 | 0.0 | - |
603
+ | 0.4154 | 21450 | 0.0 | - |
604
+ | 0.4163 | 21500 | 0.0 | - |
605
+ | 0.4173 | 21550 | 0.0 | - |
606
+ | 0.4183 | 21600 | 0.0 | - |
607
+ | 0.4192 | 21650 | 0.0 | - |
608
+ | 0.4202 | 21700 | 0.0 | - |
609
+ | 0.4212 | 21750 | 0.0 | - |
610
+ | 0.4221 | 21800 | 0.0 | - |
611
+ | 0.4231 | 21850 | 0.0 | - |
612
+ | 0.4241 | 21900 | 0.0 | - |
613
+ | 0.4250 | 21950 | 0.0 | - |
614
+ | 0.4260 | 22000 | 0.0 | - |
615
+ | 0.4270 | 22050 | 0.0 | - |
616
+ | 0.4279 | 22100 | 0.0 | - |
617
+ | 0.4289 | 22150 | 0.0 | - |
618
+ | 0.4299 | 22200 | 0.0 | - |
619
+ | 0.4308 | 22250 | 0.0 | - |
620
+ | 0.4318 | 22300 | 0.0 | - |
621
+ | 0.4328 | 22350 | 0.0 | - |
622
+ | 0.4337 | 22400 | 0.0 | - |
623
+ | 0.4347 | 22450 | 0.0 | - |
624
+ | 0.4357 | 22500 | 0.0 | - |
625
+ | 0.4367 | 22550 | 0.0 | - |
626
+ | 0.4376 | 22600 | 0.0 | - |
627
+ | 0.4386 | 22650 | 0.0 | - |
628
+ | 0.4396 | 22700 | 0.0 | - |
629
+ | 0.4405 | 22750 | 0.0 | - |
630
+ | 0.4415 | 22800 | 0.0 | - |
631
+ | 0.4425 | 22850 | 0.0 | - |
632
+ | 0.4434 | 22900 | 0.0 | - |
633
+ | 0.4444 | 22950 | 0.0 | - |
634
+ | 0.4454 | 23000 | 0.0 | - |
635
+ | 0.4463 | 23050 | 0.0 | - |
636
+ | 0.4473 | 23100 | 0.0 | - |
637
+ | 0.4483 | 23150 | 0.0 | - |
638
+ | 0.4492 | 23200 | 0.0 | - |
639
+ | 0.4502 | 23250 | 0.0 | - |
640
+ | 0.4512 | 23300 | 0.0 | - |
641
+ | 0.4521 | 23350 | 0.0 | - |
642
+ | 0.4531 | 23400 | 0.0 | - |
643
+ | 0.4541 | 23450 | 0.0 | - |
644
+ | 0.4550 | 23500 | 0.0 | - |
645
+ | 0.4560 | 23550 | 0.0 | - |
646
+ | 0.4570 | 23600 | 0.0 | - |
647
+ | 0.4580 | 23650 | 0.0 | - |
648
+ | 0.4589 | 23700 | 0.0 | - |
649
+ | 0.4599 | 23750 | 0.0 | - |
650
+ | 0.4609 | 23800 | 0.0 | - |
651
+ | 0.4618 | 23850 | 0.0 | - |
652
+ | 0.4628 | 23900 | 0.0 | - |
653
+ | 0.4638 | 23950 | 0.0 | - |
654
+ | 0.4647 | 24000 | 0.0 | - |
655
+ | 0.4657 | 24050 | 0.0 | - |
656
+ | 0.4667 | 24100 | 0.0 | - |
657
+ | 0.4676 | 24150 | 0.0 | - |
658
+ | 0.4686 | 24200 | 0.0 | - |
659
+ | 0.4696 | 24250 | 0.0 | - |
660
+ | 0.4705 | 24300 | 0.0 | - |
661
+ | 0.4715 | 24350 | 0.0 | - |
662
+ | 0.4725 | 24400 | 0.0 | - |
663
+ | 0.4734 | 24450 | 0.0 | - |
664
+ | 0.4744 | 24500 | 0.0 | - |
665
+ | 0.4754 | 24550 | 0.0 | - |
666
+ | 0.4763 | 24600 | 0.0 | - |
667
+ | 0.4773 | 24650 | 0.0 | - |
668
+ | 0.4783 | 24700 | 0.0 | - |
669
+ | 0.4793 | 24750 | 0.0 | - |
670
+ | 0.4802 | 24800 | 0.0 | - |
671
+ | 0.4812 | 24850 | 0.0 | - |
672
+ | 0.4822 | 24900 | 0.0 | - |
673
+ | 0.4831 | 24950 | 0.0 | - |
674
+ | 0.4841 | 25000 | 0.0 | - |
675
+ | 0.4851 | 25050 | 0.0 | - |
676
+ | 0.4860 | 25100 | 0.0 | - |
677
+ | 0.4870 | 25150 | 0.0 | - |
678
+ | 0.4880 | 25200 | 0.0 | - |
679
+ | 0.4889 | 25250 | 0.0 | - |
680
+ | 0.4899 | 25300 | 0.0 | - |
681
+ | 0.4909 | 25350 | 0.0 | - |
682
+ | 0.4918 | 25400 | 0.0 | - |
683
+ | 0.4928 | 25450 | 0.0 | - |
684
+ | 0.4938 | 25500 | 0.0 | - |
685
+ | 0.4947 | 25550 | 0.0 | - |
686
+ | 0.4957 | 25600 | 0.0 | - |
687
+ | 0.4967 | 25650 | 0.0 | - |
688
+ | 0.4976 | 25700 | 0.0 | - |
689
+ | 0.4986 | 25750 | 0.0 | - |
690
+ | 0.4996 | 25800 | 0.0 | - |
691
+ | 0.5006 | 25850 | 0.0 | - |
692
+ | 0.5015 | 25900 | 0.0 | - |
693
+ | 0.5025 | 25950 | 0.0 | - |
694
+ | 0.5035 | 26000 | 0.0 | - |
695
+ | 0.5044 | 26050 | 0.0 | - |
696
+ | 0.5054 | 26100 | 0.0 | - |
697
+ | 0.5064 | 26150 | 0.0 | - |
698
+ | 0.5073 | 26200 | 0.0 | - |
699
+ | 0.5083 | 26250 | 0.0 | - |
700
+ | 0.5093 | 26300 | 0.0 | - |
701
+ | 0.5102 | 26350 | 0.0 | - |
702
+ | 0.5112 | 26400 | 0.0 | - |
703
+ | 0.5122 | 26450 | 0.0 | - |
704
+ | 0.5131 | 26500 | 0.0 | - |
705
+ | 0.5141 | 26550 | 0.0 | - |
706
+ | 0.5151 | 26600 | 0.0 | - |
707
+ | 0.5160 | 26650 | 0.0 | - |
708
+ | 0.5170 | 26700 | 0.0 | - |
709
+ | 0.5180 | 26750 | 0.0 | - |
710
+ | 0.5189 | 26800 | 0.0 | - |
711
+ | 0.5199 | 26850 | 0.0 | - |
712
+ | 0.5209 | 26900 | 0.0 | - |
713
+ | 0.5219 | 26950 | 0.0 | - |
714
+ | 0.5228 | 27000 | 0.0 | - |
715
+ | 0.5238 | 27050 | 0.0 | - |
716
+ | 0.5248 | 27100 | 0.0 | - |
717
+ | 0.5257 | 27150 | 0.0 | - |
718
+ | 0.5267 | 27200 | 0.0 | - |
719
+ | 0.5277 | 27250 | 0.0 | - |
720
+ | 0.5286 | 27300 | 0.0 | - |
721
+ | 0.5296 | 27350 | 0.0 | - |
722
+ | 0.5306 | 27400 | 0.0 | - |
723
+ | 0.5315 | 27450 | 0.0 | - |
724
+ | 0.5325 | 27500 | 0.0 | - |
725
+ | 0.5335 | 27550 | 0.0 | - |
726
+ | 0.5344 | 27600 | 0.0 | - |
727
+ | 0.5354 | 27650 | 0.0 | - |
728
+ | 0.5364 | 27700 | 0.0 | - |
729
+ | 0.5373 | 27750 | 0.0 | - |
730
+ | 0.5383 | 27800 | 0.0 | - |
731
+ | 0.5393 | 27850 | 0.0 | - |
732
+ | 0.5402 | 27900 | 0.0 | - |
733
+ | 0.5412 | 27950 | 0.0 | - |
734
+ | 0.5422 | 28000 | 0.0 | - |
735
+ | 0.5432 | 28050 | 0.0 | - |
736
+ | 0.5441 | 28100 | 0.0 | - |
737
+ | 0.5451 | 28150 | 0.0 | - |
738
+ | 0.5461 | 28200 | 0.0 | - |
739
+ | 0.5470 | 28250 | 0.0 | - |
740
+ | 0.5480 | 28300 | 0.0 | - |
741
+ | 0.5490 | 28350 | 0.0 | - |
742
+ | 0.5499 | 28400 | 0.0 | - |
743
+ | 0.5509 | 28450 | 0.0 | - |
744
+ | 0.5519 | 28500 | 0.0 | - |
745
+ | 0.5528 | 28550 | 0.0 | - |
746
+ | 0.5538 | 28600 | 0.0 | - |
747
+ | 0.5548 | 28650 | 0.0 | - |
748
+ | 0.5557 | 28700 | 0.0 | - |
749
+ | 0.5567 | 28750 | 0.0 | - |
750
+ | 0.5577 | 28800 | 0.0 | - |
751
+ | 0.5586 | 28850 | 0.0 | - |
752
+ | 0.5596 | 28900 | 0.0 | - |
753
+ | 0.5606 | 28950 | 0.0 | - |
754
+ | 0.5615 | 29000 | 0.0 | - |
755
+ | 0.5625 | 29050 | 0.0 | - |
756
+ | 0.5635 | 29100 | 0.0 | - |
757
+ | 0.5645 | 29150 | 0.0 | - |
758
+ | 0.5654 | 29200 | 0.0 | - |
759
+ | 0.5664 | 29250 | 0.0 | - |
760
+ | 0.5674 | 29300 | 0.0 | - |
761
+ | 0.5683 | 29350 | 0.0 | - |
762
+ | 0.5693 | 29400 | 0.0 | - |
763
+ | 0.5703 | 29450 | 0.0 | - |
764
+ | 0.5712 | 29500 | 0.0 | - |
765
+ | 0.5722 | 29550 | 0.0 | - |
766
+ | 0.5732 | 29600 | 0.0 | - |
767
+ | 0.5741 | 29650 | 0.0 | - |
768
+ | 0.5751 | 29700 | 0.0 | - |
769
+ | 0.5761 | 29750 | 0.0 | - |
770
+ | 0.5770 | 29800 | 0.0 | - |
771
+ | 0.5780 | 29850 | 0.0 | - |
772
+ | 0.5790 | 29900 | 0.0 | - |
773
+ | 0.5799 | 29950 | 0.0 | - |
774
+ | 0.5809 | 30000 | 0.0 | - |
775
+ | 0.5819 | 30050 | 0.0 | - |
776
+ | 0.5828 | 30100 | 0.0 | - |
777
+ | 0.5838 | 30150 | 0.0 | - |
778
+ | 0.5848 | 30200 | 0.0 | - |
779
+ | 0.5858 | 30250 | 0.0 | - |
780
+ | 0.5867 | 30300 | 0.0 | - |
781
+ | 0.5877 | 30350 | 0.0 | - |
782
+ | 0.5887 | 30400 | 0.0 | - |
783
+ | 0.5896 | 30450 | 0.0 | - |
784
+ | 0.5906 | 30500 | 0.0 | - |
785
+ | 0.5916 | 30550 | 0.0 | - |
786
+ | 0.5925 | 30600 | 0.0 | - |
787
+ | 0.5935 | 30650 | 0.0 | - |
788
+ | 0.5945 | 30700 | 0.0 | - |
789
+ | 0.5954 | 30750 | 0.0 | - |
790
+ | 0.5964 | 30800 | 0.0 | - |
791
+ | 0.5974 | 30850 | 0.0 | - |
792
+ | 0.5983 | 30900 | 0.0 | - |
793
+ | 0.5993 | 30950 | 0.0 | - |
794
+ | 0.6003 | 31000 | 0.0 | - |
795
+ | 0.6012 | 31050 | 0.0 | - |
796
+ | 0.6022 | 31100 | 0.0 | - |
797
+ | 0.6032 | 31150 | 0.0 | - |
798
+ | 0.6041 | 31200 | 0.0 | - |
799
+ | 0.6051 | 31250 | 0.0 | - |
800
+ | 0.6061 | 31300 | 0.0 | - |
801
+ | 0.6071 | 31350 | 0.0 | - |
802
+ | 0.6080 | 31400 | 0.0 | - |
803
+ | 0.6090 | 31450 | 0.0 | - |
804
+ | 0.6100 | 31500 | 0.0 | - |
805
+ | 0.6109 | 31550 | 0.0 | - |
806
+ | 0.6119 | 31600 | 0.0 | - |
807
+ | 0.6129 | 31650 | 0.0 | - |
808
+ | 0.6138 | 31700 | 0.0 | - |
809
+ | 0.6148 | 31750 | 0.0 | - |
810
+ | 0.6158 | 31800 | 0.0 | - |
811
+ | 0.6167 | 31850 | 0.0 | - |
812
+ | 0.6177 | 31900 | 0.0 | - |
813
+ | 0.6187 | 31950 | 0.0 | - |
814
+ | 0.6196 | 32000 | 0.0 | - |
815
+ | 0.6206 | 32050 | 0.0 | - |
816
+ | 0.6216 | 32100 | 0.0 | - |
817
+ | 0.6225 | 32150 | 0.0 | - |
818
+ | 0.6235 | 32200 | 0.0 | - |
819
+ | 0.6245 | 32250 | 0.0 | - |
820
+ | 0.6254 | 32300 | 0.0 | - |
821
+ | 0.6264 | 32350 | 0.0 | - |
822
+ | 0.6274 | 32400 | 0.0 | - |
823
+ | 0.6284 | 32450 | 0.0 | - |
824
+ | 0.6293 | 32500 | 0.0 | - |
825
+ | 0.6303 | 32550 | 0.0 | - |
826
+ | 0.6313 | 32600 | 0.0 | - |
827
+ | 0.6322 | 32650 | 0.0 | - |
828
+ | 0.6332 | 32700 | 0.0 | - |
829
+ | 0.6342 | 32750 | 0.0 | - |
830
+ | 0.6351 | 32800 | 0.0 | - |
831
+ | 0.6361 | 32850 | 0.0 | - |
832
+ | 0.6371 | 32900 | 0.0 | - |
833
+ | 0.6380 | 32950 | 0.0 | - |
834
+ | 0.6390 | 33000 | 0.0 | - |
835
+ | 0.6400 | 33050 | 0.0 | - |
836
+ | 0.6409 | 33100 | 0.0 | - |
837
+ | 0.6419 | 33150 | 0.0 | - |
838
+ | 0.6429 | 33200 | 0.0 | - |
839
+ | 0.6438 | 33250 | 0.0 | - |
840
+ | 0.6448 | 33300 | 0.0 | - |
841
+ | 0.6458 | 33350 | 0.0 | - |
842
+ | 0.6467 | 33400 | 0.0 | - |
843
+ | 0.6477 | 33450 | 0.0 | - |
844
+ | 0.6487 | 33500 | 0.0 | - |
845
+ | 0.6497 | 33550 | 0.0 | - |
846
+ | 0.6506 | 33600 | 0.0 | - |
847
+ | 0.6516 | 33650 | 0.0 | - |
848
+ | 0.6526 | 33700 | 0.0 | - |
849
+ | 0.6535 | 33750 | 0.0 | - |
850
+ | 0.6545 | 33800 | 0.0 | - |
851
+ | 0.6555 | 33850 | 0.0 | - |
852
+ | 0.6564 | 33900 | 0.0 | - |
853
+ | 0.6574 | 33950 | 0.0 | - |
854
+ | 0.6584 | 34000 | 0.0 | - |
855
+ | 0.6593 | 34050 | 0.0 | - |
856
+ | 0.6603 | 34100 | 0.0 | - |
857
+ | 0.6613 | 34150 | 0.0 | - |
858
+ | 0.6622 | 34200 | 0.0 | - |
859
+ | 0.6632 | 34250 | 0.0 | - |
860
+ | 0.6642 | 34300 | 0.0 | - |
861
+ | 0.6651 | 34350 | 0.0 | - |
862
+ | 0.6661 | 34400 | 0.0 | - |
863
+ | 0.6671 | 34450 | 0.0 | - |
864
+ | 0.6680 | 34500 | 0.0 | - |
865
+ | 0.6690 | 34550 | 0.0 | - |
866
+ | 0.6700 | 34600 | 0.0 | - |
867
+ | 0.6710 | 34650 | 0.0 | - |
868
+ | 0.6719 | 34700 | 0.0 | - |
869
+ | 0.6729 | 34750 | 0.0 | - |
870
+ | 0.6739 | 34800 | 0.0 | - |
871
+ | 0.6748 | 34850 | 0.0 | - |
872
+ | 0.6758 | 34900 | 0.0 | - |
873
+ | 0.6768 | 34950 | 0.0 | - |
874
+ | 0.6777 | 35000 | 0.0 | - |
875
+ | 0.6787 | 35050 | 0.0 | - |
876
+ | 0.6797 | 35100 | 0.0 | - |
877
+ | 0.6806 | 35150 | 0.0 | - |
878
+ | 0.6816 | 35200 | 0.0 | - |
879
+ | 0.6826 | 35250 | 0.0 | - |
880
+ | 0.6835 | 35300 | 0.0 | - |
881
+ | 0.6845 | 35350 | 0.0 | - |
882
+ | 0.6855 | 35400 | 0.0 | - |
883
+ | 0.6864 | 35450 | 0.0 | - |
884
+ | 0.6874 | 35500 | 0.0 | - |
885
+ | 0.6884 | 35550 | 0.0 | - |
886
+ | 0.6893 | 35600 | 0.0 | - |
887
+ | 0.6903 | 35650 | 0.0 | - |
888
+ | 0.6913 | 35700 | 0.0 | - |
889
+ | 0.6923 | 35750 | 0.0 | - |
890
+ | 0.6932 | 35800 | 0.0 | - |
891
+ | 0.6942 | 35850 | 0.0 | - |
892
+ | 0.6952 | 35900 | 0.0 | - |
893
+ | 0.6961 | 35950 | 0.0 | - |
894
+ | 0.6971 | 36000 | 0.0 | - |
895
+ | 0.6981 | 36050 | 0.0 | - |
896
+ | 0.6990 | 36100 | 0.0 | - |
897
+ | 0.7000 | 36150 | 0.0 | - |
898
+ | 0.7010 | 36200 | 0.0 | - |
899
+ | 0.7019 | 36250 | 0.0 | - |
900
+ | 0.7029 | 36300 | 0.0 | - |
901
+ | 0.7039 | 36350 | 0.0 | - |
902
+ | 0.7048 | 36400 | 0.0 | - |
903
+ | 0.7058 | 36450 | 0.0 | - |
904
+ | 0.7068 | 36500 | 0.0 | - |
905
+ | 0.7077 | 36550 | 0.0 | - |
906
+ | 0.7087 | 36600 | 0.0 | - |
907
+ | 0.7097 | 36650 | 0.0 | - |
908
+ | 0.7106 | 36700 | 0.0 | - |
909
+ | 0.7116 | 36750 | 0.0 | - |
910
+ | 0.7126 | 36800 | 0.0 | - |
911
+ | 0.7136 | 36850 | 0.0 | - |
912
+ | 0.7145 | 36900 | 0.0 | - |
913
+ | 0.7155 | 36950 | 0.0 | - |
914
+ | 0.7165 | 37000 | 0.0 | - |
915
+ | 0.7174 | 37050 | 0.0 | - |
916
+ | 0.7184 | 37100 | 0.0 | - |
917
+ | 0.7194 | 37150 | 0.0 | - |
918
+ | 0.7203 | 37200 | 0.0 | - |
919
+ | 0.7213 | 37250 | 0.0 | - |
920
+ | 0.7223 | 37300 | 0.0 | - |
921
+ | 0.7232 | 37350 | 0.0 | - |
922
+ | 0.7242 | 37400 | 0.0 | - |
923
+ | 0.7252 | 37450 | 0.0 | - |
924
+ | 0.7261 | 37500 | 0.0 | - |
925
+ | 0.7271 | 37550 | 0.0 | - |
926
+ | 0.7281 | 37600 | 0.0 | - |
927
+ | 0.7290 | 37650 | 0.0 | - |
928
+ | 0.7300 | 37700 | 0.0 | - |
929
+ | 0.7310 | 37750 | 0.0 | - |
930
+ | 0.7319 | 37800 | 0.0 | - |
931
+ | 0.7329 | 37850 | 0.0 | - |
932
+ | 0.7339 | 37900 | 0.0 | - |
933
+ | 0.7349 | 37950 | 0.0 | - |
934
+ | 0.7358 | 38000 | 0.0 | - |
935
+ | 0.7368 | 38050 | 0.0 | - |
936
+ | 0.7378 | 38100 | 0.0 | - |
937
+ | 0.7387 | 38150 | 0.0 | - |
938
+ | 0.7397 | 38200 | 0.0 | - |
939
+ | 0.7407 | 38250 | 0.0 | - |
940
+ | 0.7416 | 38300 | 0.0 | - |
941
+ | 0.7426 | 38350 | 0.0 | - |
942
+ | 0.7436 | 38400 | 0.0 | - |
943
+ | 0.7445 | 38450 | 0.0 | - |
944
+ | 0.7455 | 38500 | 0.0 | - |
945
+ | 0.7465 | 38550 | 0.0 | - |
946
+ | 0.7474 | 38600 | 0.0 | - |
947
+ | 0.7484 | 38650 | 0.0 | - |
948
+ | 0.7494 | 38700 | 0.0 | - |
949
+ | 0.7503 | 38750 | 0.0 | - |
950
+ | 0.7513 | 38800 | 0.0 | - |
951
+ | 0.7523 | 38850 | 0.0 | - |
952
+ | 0.7532 | 38900 | 0.0 | - |
953
+ | 0.7542 | 38950 | 0.0 | - |
954
+ | 0.7552 | 39000 | 0.0 | - |
955
+ | 0.7562 | 39050 | 0.0 | - |
956
+ | 0.7571 | 39100 | 0.0 | - |
957
+ | 0.7581 | 39150 | 0.0 | - |
958
+ | 0.7591 | 39200 | 0.0 | - |
959
+ | 0.7600 | 39250 | 0.0 | - |
960
+ | 0.7610 | 39300 | 0.0 | - |
961
+ | 0.7620 | 39350 | 0.0 | - |
962
+ | 0.7629 | 39400 | 0.0 | - |
963
+ | 0.7639 | 39450 | 0.0 | - |
964
+ | 0.7649 | 39500 | 0.0 | - |
965
+ | 0.7658 | 39550 | 0.0 | - |
966
+ | 0.7668 | 39600 | 0.0 | - |
967
+ | 0.7678 | 39650 | 0.0 | - |
968
+ | 0.7687 | 39700 | 0.0 | - |
969
+ | 0.7697 | 39750 | 0.0 | - |
970
+ | 0.7707 | 39800 | 0.0 | - |
971
+ | 0.7716 | 39850 | 0.0 | - |
972
+ | 0.7726 | 39900 | 0.0 | - |
973
+ | 0.7736 | 39950 | 0.0 | - |
974
+ | 0.7745 | 40000 | 0.0 | - |
975
+ | 0.7755 | 40050 | 0.0 | - |
976
+ | 0.7765 | 40100 | 0.0 | - |
977
+ | 0.7775 | 40150 | 0.0 | - |
978
+ | 0.7784 | 40200 | 0.0 | - |
979
+ | 0.7794 | 40250 | 0.0 | - |
980
+ | 0.7804 | 40300 | 0.0 | - |
981
+ | 0.7813 | 40350 | 0.0 | - |
982
+ | 0.7823 | 40400 | 0.0 | - |
983
+ | 0.7833 | 40450 | 0.0 | - |
984
+ | 0.7842 | 40500 | 0.0 | - |
985
+ | 0.7852 | 40550 | 0.0 | - |
986
+ | 0.7862 | 40600 | 0.0 | - |
987
+ | 0.7871 | 40650 | 0.0 | - |
988
+ | 0.7881 | 40700 | 0.0 | - |
989
+ | 0.7891 | 40750 | 0.0 | - |
990
+ | 0.7900 | 40800 | 0.0 | - |
991
+ | 0.7910 | 40850 | 0.0 | - |
992
+ | 0.7920 | 40900 | 0.0 | - |
993
+ | 0.7929 | 40950 | 0.0 | - |
994
+ | 0.7939 | 41000 | 0.0 | - |
995
+ | 0.7949 | 41050 | 0.0 | - |
996
+ | 0.7958 | 41100 | 0.0 | - |
997
+ | 0.7968 | 41150 | 0.0 | - |
998
+ | 0.7978 | 41200 | 0.0 | - |
999
+ | 0.7988 | 41250 | 0.0 | - |
1000
+ | 0.7997 | 41300 | 0.0 | - |
1001
+ | 0.8007 | 41350 | 0.0 | - |
1002
+ | 0.8017 | 41400 | 0.0 | - |
1003
+ | 0.8026 | 41450 | 0.0 | - |
1004
+ | 0.8036 | 41500 | 0.0 | - |
1005
+ | 0.8046 | 41550 | 0.0 | - |
1006
+ | 0.8055 | 41600 | 0.0 | - |
1007
+ | 0.8065 | 41650 | 0.0 | - |
1008
+ | 0.8075 | 41700 | 0.0 | - |
1009
+ | 0.8084 | 41750 | 0.0 | - |
1010
+ | 0.8094 | 41800 | 0.0 | - |
1011
+ | 0.8104 | 41850 | 0.0 | - |
1012
+ | 0.8113 | 41900 | 0.0 | - |
1013
+ | 0.8123 | 41950 | 0.0 | - |
1014
+ | 0.8133 | 42000 | 0.0 | - |
1015
+ | 0.8142 | 42050 | 0.0 | - |
1016
+ | 0.8152 | 42100 | 0.0 | - |
1017
+ | 0.8162 | 42150 | 0.0 | - |
1018
+ | 0.8171 | 42200 | 0.0 | - |
1019
+ | 0.8181 | 42250 | 0.0 | - |
1020
+ | 0.8191 | 42300 | 0.0 | - |
1021
+ | 0.8201 | 42350 | 0.0 | - |
1022
+ | 0.8210 | 42400 | 0.0 | - |
1023
+ | 0.8220 | 42450 | 0.0 | - |
1024
+ | 0.8230 | 42500 | 0.0 | - |
1025
+ | 0.8239 | 42550 | 0.0 | - |
1026
+ | 0.8249 | 42600 | 0.0 | - |
1027
+ | 0.8259 | 42650 | 0.0 | - |
1028
+ | 0.8268 | 42700 | 0.0 | - |
1029
+ | 0.8278 | 42750 | 0.0 | - |
1030
+ | 0.8288 | 42800 | 0.0 | - |
1031
+ | 0.8297 | 42850 | 0.0 | - |
1032
+ | 0.8307 | 42900 | 0.0 | - |
1033
+ | 0.8317 | 42950 | 0.0 | - |
1034
+ | 0.8326 | 43000 | 0.0 | - |
1035
+ | 0.8336 | 43050 | 0.0 | - |
1036
+ | 0.8346 | 43100 | 0.0 | - |
1037
+ | 0.8355 | 43150 | 0.0 | - |
1038
+ | 0.8365 | 43200 | 0.0 | - |
1039
+ | 0.8375 | 43250 | 0.0 | - |
1040
+ | 0.8384 | 43300 | 0.0 | - |
1041
+ | 0.8394 | 43350 | 0.0 | - |
1042
+ | 0.8404 | 43400 | 0.0 | - |
1043
+ | 0.8414 | 43450 | 0.0 | - |
1044
+ | 0.8423 | 43500 | 0.0 | - |
1045
+ | 0.8433 | 43550 | 0.0 | - |
1046
+ | 0.8443 | 43600 | 0.0 | - |
1047
+ | 0.8452 | 43650 | 0.0 | - |
1048
+ | 0.8462 | 43700 | 0.0 | - |
1049
+ | 0.8472 | 43750 | 0.0 | - |
1050
+ | 0.8481 | 43800 | 0.0 | - |
1051
+ | 0.8491 | 43850 | 0.0 | - |
1052
+ | 0.8501 | 43900 | 0.0 | - |
1053
+ | 0.8510 | 43950 | 0.0 | - |
1054
+ | 0.8520 | 44000 | 0.0 | - |
1055
+ | 0.8530 | 44050 | 0.0 | - |
1056
+ | 0.8539 | 44100 | 0.0 | - |
1057
+ | 0.8549 | 44150 | 0.0 | - |
1058
+ | 0.8559 | 44200 | 0.0 | - |
1059
+ | 0.8568 | 44250 | 0.0 | - |
1060
+ | 0.8578 | 44300 | 0.0 | - |
1061
+ | 0.8588 | 44350 | 0.0 | - |
1062
+ | 0.8597 | 44400 | 0.0 | - |
1063
+ | 0.8607 | 44450 | 0.0 | - |
1064
+ | 0.8617 | 44500 | 0.0 | - |
1065
+ | 0.8627 | 44550 | 0.0 | - |
1066
+ | 0.8636 | 44600 | 0.0 | - |
1067
+ | 0.8646 | 44650 | 0.0 | - |
1068
+ | 0.8656 | 44700 | 0.0 | - |
1069
+ | 0.8665 | 44750 | 0.0 | - |
1070
+ | 0.8675 | 44800 | 0.0 | - |
1071
+ | 0.8685 | 44850 | 0.0 | - |
1072
+ | 0.8694 | 44900 | 0.0 | - |
1073
+ | 0.8704 | 44950 | 0.0 | - |
1074
+ | 0.8714 | 45000 | 0.0 | - |
1075
+ | 0.8723 | 45050 | 0.0 | - |
1076
+ | 0.8733 | 45100 | 0.0 | - |
1077
+ | 0.8743 | 45150 | 0.0 | - |
1078
+ | 0.8752 | 45200 | 0.0 | - |
1079
+ | 0.8762 | 45250 | 0.0 | - |
1080
+ | 0.8772 | 45300 | 0.0 | - |
1081
+ | 0.8781 | 45350 | 0.0 | - |
1082
+ | 0.8791 | 45400 | 0.0 | - |
1083
+ | 0.8801 | 45450 | 0.0 | - |
1084
+ | 0.8810 | 45500 | 0.0 | - |
1085
+ | 0.8820 | 45550 | 0.0 | - |
1086
+ | 0.8830 | 45600 | 0.0 | - |
1087
+ | 0.8840 | 45650 | 0.0 | - |
1088
+ | 0.8849 | 45700 | 0.0 | - |
1089
+ | 0.8859 | 45750 | 0.0 | - |
1090
+ | 0.8869 | 45800 | 0.0 | - |
1091
+ | 0.8878 | 45850 | 0.0 | - |
1092
+ | 0.8888 | 45900 | 0.0 | - |
1093
+ | 0.8898 | 45950 | 0.0 | - |
1094
+ | 0.8907 | 46000 | 0.0 | - |
1095
+ | 0.8917 | 46050 | 0.0 | - |
1096
+ | 0.8927 | 46100 | 0.0 | - |
1097
+ | 0.8936 | 46150 | 0.0 | - |
1098
+ | 0.8946 | 46200 | 0.0 | - |
1099
+ | 0.8956 | 46250 | 0.0 | - |
1100
+ | 0.8965 | 46300 | 0.0 | - |
1101
+ | 0.8975 | 46350 | 0.0 | - |
1102
+ | 0.8985 | 46400 | 0.0 | - |
1103
+ | 0.8994 | 46450 | 0.0 | - |
1104
+ | 0.9004 | 46500 | 0.0 | - |
1105
+ | 0.9014 | 46550 | 0.0 | - |
1106
+ | 0.9023 | 46600 | 0.0 | - |
1107
+ | 0.9033 | 46650 | 0.0 | - |
1108
+ | 0.9043 | 46700 | 0.0 | - |
1109
+ | 0.9053 | 46750 | 0.0 | - |
1110
+ | 0.9062 | 46800 | 0.0 | - |
1111
+ | 0.9072 | 46850 | 0.0 | - |
1112
+ | 0.9082 | 46900 | 0.0 | - |
1113
+ | 0.9091 | 46950 | 0.0 | - |
1114
+ | 0.9101 | 47000 | 0.0 | - |
1115
+ | 0.9111 | 47050 | 0.0 | - |
1116
+ | 0.9120 | 47100 | 0.0 | - |
1117
+ | 0.9130 | 47150 | 0.0 | - |
1118
+ | 0.9140 | 47200 | 0.0 | - |
1119
+ | 0.9149 | 47250 | 0.0 | - |
1120
+ | 0.9159 | 47300 | 0.0 | - |
1121
+ | 0.9169 | 47350 | 0.0 | - |
1122
+ | 0.9178 | 47400 | 0.0 | - |
1123
+ | 0.9188 | 47450 | 0.0 | - |
1124
+ | 0.9198 | 47500 | 0.0 | - |
1125
+ | 0.9207 | 47550 | 0.0 | - |
1126
+ | 0.9217 | 47600 | 0.0 | - |
1127
+ | 0.9227 | 47650 | 0.0 | - |
1128
+ | 0.9236 | 47700 | 0.0 | - |
1129
+ | 0.9246 | 47750 | 0.0 | - |
1130
+ | 0.9256 | 47800 | 0.0 | - |
1131
+ | 0.9266 | 47850 | 0.0 | - |
1132
+ | 0.9275 | 47900 | 0.0 | - |
1133
+ | 0.9285 | 47950 | 0.0 | - |
1134
+ | 0.9295 | 48000 | 0.0 | - |
1135
+ | 0.9304 | 48050 | 0.0 | - |
1136
+ | 0.9314 | 48100 | 0.0 | - |
1137
+ | 0.9324 | 48150 | 0.0 | - |
1138
+ | 0.9333 | 48200 | 0.0 | - |
1139
+ | 0.9343 | 48250 | 0.0 | - |
1140
+ | 0.9353 | 48300 | 0.0 | - |
1141
+ | 0.9362 | 48350 | 0.0 | - |
1142
+ | 0.9372 | 48400 | 0.0 | - |
1143
+ | 0.9382 | 48450 | 0.0 | - |
1144
+ | 0.9391 | 48500 | 0.0 | - |
1145
+ | 0.9401 | 48550 | 0.0 | - |
1146
+ | 0.9411 | 48600 | 0.0 | - |
1147
+ | 0.9420 | 48650 | 0.0 | - |
1148
+ | 0.9430 | 48700 | 0.0 | - |
1149
+ | 0.9440 | 48750 | 0.0 | - |
1150
+ | 0.9449 | 48800 | 0.0 | - |
1151
+ | 0.9459 | 48850 | 0.0 | - |
1152
+ | 0.9469 | 48900 | 0.0 | - |
1153
+ | 0.9479 | 48950 | 0.0 | - |
1154
+ | 0.9488 | 49000 | 0.0 | - |
1155
+ | 0.9498 | 49050 | 0.0 | - |
1156
+ | 0.9508 | 49100 | 0.0 | - |
1157
+ | 0.9517 | 49150 | 0.0 | - |
1158
+ | 0.9527 | 49200 | 0.0 | - |
1159
+ | 0.9537 | 49250 | 0.0 | - |
1160
+ | 0.9546 | 49300 | 0.0 | - |
1161
+ | 0.9556 | 49350 | 0.0 | - |
1162
+ | 0.9566 | 49400 | 0.0 | - |
1163
+ | 0.9575 | 49450 | 0.0 | - |
1164
+ | 0.9585 | 49500 | 0.0 | - |
1165
+ | 0.9595 | 49550 | 0.0 | - |
1166
+ | 0.9604 | 49600 | 0.0 | - |
1167
+ | 0.9614 | 49650 | 0.0 | - |
1168
+ | 0.9624 | 49700 | 0.0 | - |
1169
+ | 0.9633 | 49750 | 0.0 | - |
1170
+ | 0.9643 | 49800 | 0.0 | - |
1171
+ | 0.9653 | 49850 | 0.0 | - |
1172
+ | 0.9662 | 49900 | 0.0 | - |
1173
+ | 0.9672 | 49950 | 0.0 | - |
1174
+ | 0.9682 | 50000 | 0.0 | - |
1175
+ | 0.9692 | 50050 | 0.0 | - |
1176
+ | 0.9701 | 50100 | 0.0 | - |
1177
+ | 0.9711 | 50150 | 0.0 | - |
1178
+ | 0.9721 | 50200 | 0.0 | - |
1179
+ | 0.9730 | 50250 | 0.0 | - |
1180
+ | 0.9740 | 50300 | 0.0 | - |
1181
+ | 0.9750 | 50350 | 0.0 | - |
1182
+ | 0.9759 | 50400 | 0.0 | - |
1183
+ | 0.9769 | 50450 | 0.0 | - |
1184
+ | 0.9779 | 50500 | 0.0 | - |
1185
+ | 0.9788 | 50550 | 0.0 | - |
1186
+ | 0.9798 | 50600 | 0.0 | - |
1187
+ | 0.9808 | 50650 | 0.0 | - |
1188
+ | 0.9817 | 50700 | 0.0 | - |
1189
+ | 0.9827 | 50750 | 0.0 | - |
1190
+ | 0.9837 | 50800 | 0.0 | - |
1191
+ | 0.9846 | 50850 | 0.0 | - |
1192
+ | 0.9856 | 50900 | 0.0 | - |
1193
+ | 0.9866 | 50950 | 0.0 | - |
1194
+ | 0.9875 | 51000 | 0.0 | - |
1195
+ | 0.9885 | 51050 | 0.0 | - |
1196
+ | 0.9895 | 51100 | 0.0 | - |
1197
+ | 0.9905 | 51150 | 0.0 | - |
1198
+ | 0.9914 | 51200 | 0.0 | - |
1199
+ | 0.9924 | 51250 | 0.0 | - |
1200
+ | 0.9934 | 51300 | 0.0 | - |
1201
+ | 0.9943 | 51350 | 0.0 | - |
1202
+ | 0.9953 | 51400 | 0.0 | - |
1203
+ | 0.9963 | 51450 | 0.0 | - |
1204
+ | 0.9972 | 51500 | 0.0 | - |
1205
+ | 0.9982 | 51550 | 0.0 | - |
1206
+ | 0.9992 | 51600 | 0.0 | - |
1207
+
1208
+ ### Framework Versions
1209
+ - Python: 3.10.12
1210
+ - SetFit: 1.1.0
1211
+ - Sentence Transformers: 3.3.1
1212
+ - Transformers: 4.42.2
1213
+ - PyTorch: 2.5.1+cu121
1214
+ - Datasets: 3.2.0
1215
+ - Tokenizers: 0.19.1
1216
+
1217
+ ## Citation
1218
+
1219
+ ### BibTeX
1220
+ ```bibtex
1221
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
1222
+ doi = {10.48550/ARXIV.2209.11055},
1223
+ url = {https://arxiv.org/abs/2209.11055},
1224
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
1225
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
1226
+ title = {Efficient Few-Shot Learning Without Prompts},
1227
+ publisher = {arXiv},
1228
+ year = {2022},
1229
+ copyright = {Creative Commons Attribution 4.0 International}
1230
+ }
1231
+ ```
1232
+
1233
+ <!--
1234
+ ## Glossary
1235
+
1236
+ *Clearly define terms in order to be accessible across audiences.*
1237
+ -->
1238
+
1239
+ <!--
1240
+ ## Model Card Authors
1241
+
1242
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
1243
+ -->
1244
+
1245
+ <!--
1246
+ ## Model Card Contact
1247
+
1248
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
1249
+ -->
config.json ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "gradient_checkpointing": false,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 384,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 1536,
14
+ "layer_norm_eps": 1e-12,
15
+ "max_position_embeddings": 512,
16
+ "model_type": "bert",
17
+ "num_attention_heads": 12,
18
+ "num_hidden_layers": 12,
19
+ "pad_token_id": 0,
20
+ "position_embedding_type": "absolute",
21
+ "torch_dtype": "float32",
22
+ "transformers_version": "4.42.2",
23
+ "type_vocab_size": 2,
24
+ "use_cache": true,
25
+ "vocab_size": 250037
26
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.3.1",
4
+ "transformers": "4.42.2",
5
+ "pytorch": "2.5.1+cu121"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": "cosine"
10
+ }
config_setfit.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "labels": [
3
+ "neutral",
4
+ "opposed",
5
+ "supportive"
6
+ ],
7
+ "normalize_embeddings": false
8
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:acfc1c2a63b308ac0c635b3df450ffd25807f70b038795d32888123a2fc250f4
3
+ size 470637416
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:41e387b96a3fa990e777923f66be5c1072937839b01d986f2aa60d0633165193
3
+ size 10207
modules.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "idx": 0,
4
+ "name": "0",
5
+ "path": "",
6
+ "type": "sentence_transformers.models.Transformer"
7
+ },
8
+ {
9
+ "idx": 1,
10
+ "name": "1",
11
+ "path": "1_Pooling",
12
+ "type": "sentence_transformers.models.Pooling"
13
+ }
14
+ ]
sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 128,
3
+ "do_lower_case": false
4
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "cls_token": {
10
+ "content": "<s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "eos_token": {
17
+ "content": "</s>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "mask_token": {
24
+ "content": "<mask>",
25
+ "lstrip": true,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "pad_token": {
31
+ "content": "<pad>",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ },
37
+ "sep_token": {
38
+ "content": "</s>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false
43
+ },
44
+ "unk_token": {
45
+ "content": "<unk>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false
50
+ }
51
+ }
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cad551d5600a84242d0973327029452a1e3672ba6313c2a3c3d69c4310e12719
3
+ size 17082987
tokenizer_config.json ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<s>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "<pad>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "</s>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "250001": {
36
+ "content": "<mask>",
37
+ "lstrip": true,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "bos_token": "<s>",
45
+ "clean_up_tokenization_spaces": true,
46
+ "cls_token": "<s>",
47
+ "do_lower_case": true,
48
+ "eos_token": "</s>",
49
+ "mask_token": "<mask>",
50
+ "max_length": 128,
51
+ "model_max_length": 128,
52
+ "pad_to_multiple_of": null,
53
+ "pad_token": "<pad>",
54
+ "pad_token_type_id": 0,
55
+ "padding_side": "right",
56
+ "sep_token": "</s>",
57
+ "stride": 0,
58
+ "strip_accents": null,
59
+ "tokenize_chinese_chars": true,
60
+ "tokenizer_class": "BertTokenizer",
61
+ "truncation_side": "right",
62
+ "truncation_strategy": "longest_first",
63
+ "unk_token": "<unk>"
64
+ }
unigram.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:da145b5e7700ae40f16691ec32a0b1fdc1ee3298db22a31ea55f57a966c4a65d
3
+ size 14763260