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legal-NER

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README.md CHANGED
@@ -21,21 +21,21 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
- - Loss: 0.0922
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- - Accuracy: 0.9840
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- - Precision: 0.9221
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- - Recall: 0.9260
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- - F1: 0.9240
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  - Classification Report: precision recall f1-score support
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31
  LOC 0.94 0.96 0.95 1837
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- MISC 0.88 0.87 0.87 922
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- ORG 0.88 0.87 0.88 1341
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- PER 0.96 0.96 0.96 1842
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- micro avg 0.92 0.93 0.92 5942
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- macro avg 0.91 0.91 0.91 5942
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- weighted avg 0.92 0.93 0.92 5942
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  ## Model description
@@ -68,209 +68,209 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Classification Report |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
71
- | 0.1354 | 0.2668 | 500 | 0.1185 | 0.9686 | 0.8405 | 0.8304 | 0.8354 | precision recall f1-score support
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- LOC 0.83 0.94 0.88 1837
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- MISC 0.78 0.70 0.74 922
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- ORG 0.81 0.62 0.70 1341
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- PER 0.90 0.94 0.92 1842
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- micro avg 0.84 0.83 0.84 5942
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- macro avg 0.83 0.80 0.81 5942
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- weighted avg 0.84 0.83 0.83 5942
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  |
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- | 0.0971 | 0.5336 | 1000 | 0.1045 | 0.9744 | 0.8578 | 0.8721 | 0.8649 | precision recall f1-score support
83
 
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- LOC 0.86 0.96 0.91 1837
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- MISC 0.89 0.71 0.79 922
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- ORG 0.78 0.74 0.76 1341
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- PER 0.89 0.96 0.93 1842
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- micro avg 0.86 0.87 0.86 5942
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  macro avg 0.86 0.84 0.85 5942
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  weighted avg 0.86 0.87 0.86 5942
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  |
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- | 0.097 | 0.8004 | 1500 | 0.0849 | 0.9776 | 0.8884 | 0.8812 | 0.8848 | precision recall f1-score support
94
 
95
- LOC 0.93 0.91 0.92 1837
96
- MISC 0.77 0.82 0.79 922
97
- ORG 0.82 0.83 0.82 1341
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- PER 0.96 0.92 0.94 1842
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100
  micro avg 0.89 0.88 0.88 5942
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- macro avg 0.87 0.87 0.87 5942
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  weighted avg 0.89 0.88 0.89 5942
103
  |
104
- | 0.0522 | 1.0672 | 2000 | 0.0838 | 0.9791 | 0.9014 | 0.8955 | 0.8984 | precision recall f1-score support
105
 
106
  LOC 0.93 0.95 0.94 1837
107
- MISC 0.82 0.81 0.82 922
108
- ORG 0.88 0.79 0.83 1341
109
- PER 0.93 0.97 0.95 1842
110
-
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- micro avg 0.90 0.90 0.90 5942
112
- macro avg 0.89 0.88 0.88 5942
113
- weighted avg 0.90 0.90 0.90 5942
114
- |
115
- | 0.0491 | 1.3340 | 2500 | 0.0734 | 0.9814 | 0.9021 | 0.9088 | 0.9054 | precision recall f1-score support
116
-
117
- LOC 0.92 0.95 0.93 1837
118
- MISC 0.86 0.82 0.84 922
119
- ORG 0.84 0.85 0.84 1341
120
- PER 0.95 0.96 0.96 1842
121
 
122
  micro avg 0.90 0.91 0.91 5942
123
  macro avg 0.89 0.89 0.89 5942
124
  weighted avg 0.90 0.91 0.91 5942
125
  |
126
- | 0.0435 | 1.6009 | 3000 | 0.0891 | 0.9776 | 0.8685 | 0.8972 | 0.8826 | precision recall f1-score support
127
 
128
- LOC 0.93 0.94 0.94 1837
129
- MISC 0.78 0.82 0.80 922
130
- ORG 0.74 0.90 0.81 1341
131
- PER 0.97 0.89 0.93 1842
132
-
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- micro avg 0.87 0.90 0.88 5942
134
- macro avg 0.86 0.89 0.87 5942
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- weighted avg 0.88 0.90 0.89 5942
136
- |
137
- | 0.0341 | 1.8677 | 3500 | 0.0777 | 0.9813 | 0.9072 | 0.9111 | 0.9092 | precision recall f1-score support
138
-
139
- LOC 0.91 0.96 0.94 1837
140
- MISC 0.87 0.84 0.85 922
141
- ORG 0.86 0.83 0.85 1341
142
- PER 0.95 0.96 0.95 1842
143
 
144
  micro avg 0.91 0.91 0.91 5942
145
  macro avg 0.90 0.90 0.90 5942
146
  weighted avg 0.91 0.91 0.91 5942
147
  |
148
- | 0.0246 | 2.1345 | 4000 | 0.0838 | 0.9813 | 0.8991 | 0.9174 | 0.9081 | precision recall f1-score support
149
 
150
- LOC 0.92 0.96 0.94 1837
151
- MISC 0.86 0.82 0.84 922
152
- ORG 0.87 0.85 0.86 1341
153
- PER 0.92 0.97 0.95 1842
154
 
155
- micro avg 0.90 0.92 0.91 5942
156
- macro avg 0.89 0.90 0.90 5942
157
- weighted avg 0.90 0.92 0.91 5942
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  |
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- | 0.0205 | 2.4013 | 4500 | 0.0764 | 0.9830 | 0.9104 | 0.9204 | 0.9154 | precision recall f1-score support
160
 
161
- LOC 0.96 0.94 0.95 1837
162
- MISC 0.84 0.86 0.85 922
163
- ORG 0.82 0.88 0.85 1341
164
- PER 0.96 0.96 0.96 1842
165
 
166
- micro avg 0.91 0.92 0.92 5942
167
- macro avg 0.90 0.91 0.90 5942
168
- weighted avg 0.91 0.92 0.92 5942
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  |
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- | 0.022 | 2.6681 | 5000 | 0.0856 | 0.9819 | 0.9051 | 0.9192 | 0.9121 | precision recall f1-score support
171
 
172
  LOC 0.92 0.96 0.94 1837
173
- MISC 0.87 0.84 0.85 922
174
- ORG 0.85 0.85 0.85 1341
175
- PER 0.95 0.97 0.96 1842
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177
- micro avg 0.91 0.92 0.91 5942
178
- macro avg 0.90 0.90 0.90 5942
179
- weighted avg 0.90 0.92 0.91 5942
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  |
181
- | 0.0244 | 2.9349 | 5500 | 0.0850 | 0.9829 | 0.9142 | 0.9194 | 0.9168 | precision recall f1-score support
182
 
183
- LOC 0.94 0.96 0.95 1837
184
  MISC 0.88 0.84 0.86 922
185
- ORG 0.86 0.85 0.86 1341
186
- PER 0.95 0.96 0.95 1842
187
 
188
- micro avg 0.91 0.92 0.92 5942
189
- macro avg 0.91 0.91 0.91 5942
190
- weighted avg 0.91 0.92 0.92 5942
191
  |
192
- | 0.0166 | 3.2017 | 6000 | 0.0861 | 0.9834 | 0.9187 | 0.9191 | 0.9189 | precision recall f1-score support
193
 
194
- LOC 0.94 0.96 0.95 1837
195
- MISC 0.90 0.84 0.87 922
196
  ORG 0.86 0.87 0.87 1341
197
- PER 0.94 0.96 0.95 1842
198
 
199
- micro avg 0.92 0.92 0.92 5942
200
- macro avg 0.91 0.91 0.91 5942
201
- weighted avg 0.92 0.92 0.92 5942
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  |
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- | 0.0094 | 3.4685 | 6500 | 0.0905 | 0.9840 | 0.9202 | 0.9236 | 0.9219 | precision recall f1-score support
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205
- LOC 0.95 0.96 0.95 1837
206
- MISC 0.89 0.86 0.88 922
207
- ORG 0.85 0.88 0.86 1341
208
- PER 0.96 0.95 0.96 1842
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- micro avg 0.92 0.92 0.92 5942
211
- macro avg 0.91 0.91 0.91 5942
212
- weighted avg 0.92 0.92 0.92 5942
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  |
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- | 0.0123 | 3.7353 | 7000 | 0.0927 | 0.9837 | 0.9239 | 0.9219 | 0.9229 | precision recall f1-score support
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216
- LOC 0.95 0.95 0.95 1837
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- MISC 0.86 0.85 0.86 922
218
- ORG 0.90 0.87 0.88 1341
219
  PER 0.95 0.97 0.96 1842
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- micro avg 0.92 0.92 0.92 5942
222
- macro avg 0.91 0.91 0.91 5942
223
- weighted avg 0.92 0.92 0.92 5942
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  |
225
- | 0.0097 | 4.0021 | 7500 | 0.0947 | 0.9839 | 0.9279 | 0.9221 | 0.9250 | precision recall f1-score support
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227
- LOC 0.95 0.96 0.95 1837
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- MISC 0.88 0.85 0.87 922
229
- ORG 0.90 0.86 0.88 1341
230
- PER 0.95 0.96 0.96 1842
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232
- micro avg 0.93 0.92 0.92 5942
233
- macro avg 0.92 0.91 0.91 5942
234
- weighted avg 0.93 0.92 0.92 5942
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  |
236
- | 0.0049 | 4.2689 | 8000 | 0.0903 | 0.9840 | 0.9248 | 0.9251 | 0.9250 | precision recall f1-score support
237
 
238
  LOC 0.94 0.96 0.95 1837
239
- MISC 0.90 0.85 0.87 922
240
- ORG 0.87 0.88 0.88 1341
241
  PER 0.95 0.96 0.96 1842
242
 
243
- micro avg 0.92 0.93 0.92 5942
244
  macro avg 0.92 0.91 0.91 5942
245
- weighted avg 0.92 0.93 0.92 5942
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  |
247
- | 0.0037 | 4.5358 | 8500 | 0.0903 | 0.9843 | 0.9235 | 0.9283 | 0.9259 | precision recall f1-score support
248
 
249
- LOC 0.94 0.96 0.95 1837
250
- MISC 0.89 0.86 0.88 922
251
- ORG 0.88 0.88 0.88 1341
252
  PER 0.95 0.96 0.96 1842
253
 
 
 
 
 
 
 
 
 
 
 
 
254
  micro avg 0.92 0.93 0.93 5942
255
  macro avg 0.92 0.92 0.92 5942
256
  weighted avg 0.92 0.93 0.93 5942
257
  |
258
- | 0.0038 | 4.8026 | 9000 | 0.0922 | 0.9840 | 0.9221 | 0.9260 | 0.9240 | precision recall f1-score support
 
 
 
 
 
 
 
 
 
 
 
259
 
260
  LOC 0.94 0.96 0.95 1837
261
- MISC 0.88 0.87 0.87 922
262
- ORG 0.88 0.87 0.88 1341
263
- PER 0.96 0.96 0.96 1842
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- micro avg 0.92 0.93 0.92 5942
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- macro avg 0.91 0.91 0.91 5942
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- weighted avg 0.92 0.93 0.92 5942
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  |
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  ### Framework versions
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  - Transformers 4.47.1
274
- - Pytorch 2.3.1+cpu
275
  - Datasets 3.2.0
276
  - Tokenizers 0.21.0
 
21
 
22
  This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.0887
25
+ - Accuracy: 0.9845
26
+ - Precision: 0.9232
27
+ - Recall: 0.9286
28
+ - F1: 0.9259
29
  - Classification Report: precision recall f1-score support
30
 
31
  LOC 0.94 0.96 0.95 1837
32
+ MISC 0.87 0.87 0.87 922
33
+ ORG 0.89 0.88 0.89 1341
34
+ PER 0.95 0.96 0.96 1842
35
 
36
+ micro avg 0.92 0.93 0.93 5942
37
+ macro avg 0.91 0.92 0.92 5942
38
+ weighted avg 0.92 0.93 0.93 5942
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40
 
41
  ## Model description
 
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69
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Classification Report |
70
  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
71
+ | 0.1403 | 0.2668 | 500 | 0.1145 | 0.9685 | 0.8296 | 0.8334 | 0.8315 | precision recall f1-score support
72
 
73
+ LOC 0.85 0.93 0.89 1837
74
+ MISC 0.72 0.79 0.75 922
75
+ ORG 0.81 0.57 0.67 1341
76
+ PER 0.87 0.95 0.91 1842
77
 
78
+ micro avg 0.83 0.83 0.83 5942
79
+ macro avg 0.81 0.81 0.80 5942
80
+ weighted avg 0.83 0.83 0.82 5942
81
  |
82
+ | 0.0978 | 0.5336 | 1000 | 0.1046 | 0.9734 | 0.8630 | 0.8679 | 0.8654 | precision recall f1-score support
83
 
84
+ LOC 0.85 0.94 0.89 1837
85
+ MISC 0.89 0.69 0.78 922
86
+ ORG 0.78 0.77 0.77 1341
87
+ PER 0.92 0.96 0.94 1842
88
 
89
+ micro avg 0.86 0.87 0.87 5942
90
  macro avg 0.86 0.84 0.85 5942
91
  weighted avg 0.86 0.87 0.86 5942
92
  |
93
+ | 0.1052 | 0.8004 | 1500 | 0.0852 | 0.9770 | 0.8901 | 0.8782 | 0.8841 | precision recall f1-score support
94
 
95
+ LOC 0.94 0.91 0.92 1837
96
+ MISC 0.85 0.77 0.81 922
97
+ ORG 0.77 0.86 0.82 1341
98
+ PER 0.96 0.91 0.93 1842
99
 
100
  micro avg 0.89 0.88 0.88 5942
101
+ macro avg 0.88 0.86 0.87 5942
102
  weighted avg 0.89 0.88 0.89 5942
103
  |
104
+ | 0.0532 | 1.0672 | 2000 | 0.0779 | 0.9810 | 0.9041 | 0.9091 | 0.9066 | precision recall f1-score support
105
 
106
  LOC 0.93 0.95 0.94 1837
107
+ MISC 0.83 0.80 0.81 922
108
+ ORG 0.85 0.86 0.86 1341
109
+ PER 0.95 0.96 0.95 1842
 
 
 
 
 
 
 
 
 
 
 
110
 
111
  micro avg 0.90 0.91 0.91 5942
112
  macro avg 0.89 0.89 0.89 5942
113
  weighted avg 0.90 0.91 0.91 5942
114
  |
115
+ | 0.0507 | 1.3340 | 2500 | 0.0739 | 0.9819 | 0.9094 | 0.9073 | 0.9083 | precision recall f1-score support
116
 
117
+ LOC 0.95 0.93 0.94 1837
118
+ MISC 0.84 0.86 0.85 922
119
+ ORG 0.87 0.83 0.85 1341
120
+ PER 0.93 0.96 0.95 1842
 
 
 
 
 
 
 
 
 
 
 
121
 
122
  micro avg 0.91 0.91 0.91 5942
123
  macro avg 0.90 0.90 0.90 5942
124
  weighted avg 0.91 0.91 0.91 5942
125
  |
126
+ | 0.0451 | 1.6009 | 3000 | 0.0816 | 0.9791 | 0.8883 | 0.9022 | 0.8952 | precision recall f1-score support
127
 
128
+ LOC 0.92 0.94 0.93 1837
129
+ MISC 0.81 0.81 0.81 922
130
+ ORG 0.80 0.88 0.84 1341
131
+ PER 0.96 0.93 0.95 1842
132
 
133
+ micro avg 0.89 0.90 0.90 5942
134
+ macro avg 0.88 0.89 0.88 5942
135
+ weighted avg 0.89 0.90 0.90 5942
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  |
137
+ | 0.0397 | 1.8677 | 3500 | 0.0755 | 0.9812 | 0.9033 | 0.9135 | 0.9084 | precision recall f1-score support
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139
+ LOC 0.90 0.96 0.93 1837
140
+ MISC 0.83 0.86 0.85 922
141
+ ORG 0.88 0.83 0.86 1341
142
+ PER 0.95 0.95 0.95 1842
143
 
144
+ micro avg 0.90 0.91 0.91 5942
145
+ macro avg 0.89 0.90 0.90 5942
146
+ weighted avg 0.90 0.91 0.91 5942
147
  |
148
+ | 0.0211 | 2.1345 | 4000 | 0.0895 | 0.9814 | 0.9173 | 0.9130 | 0.9151 | precision recall f1-score support
149
 
150
  LOC 0.92 0.96 0.94 1837
151
+ MISC 0.88 0.83 0.86 922
152
+ ORG 0.88 0.86 0.87 1341
153
+ PER 0.96 0.95 0.95 1842
154
 
155
+ micro avg 0.92 0.91 0.92 5942
156
+ macro avg 0.91 0.90 0.90 5942
157
+ weighted avg 0.92 0.91 0.91 5942
158
  |
159
+ | 0.0224 | 2.4013 | 4500 | 0.0840 | 0.9815 | 0.9005 | 0.9110 | 0.9057 | precision recall f1-score support
160
 
161
+ LOC 0.92 0.95 0.93 1837
162
  MISC 0.88 0.84 0.86 922
163
+ ORG 0.82 0.88 0.85 1341
164
+ PER 0.96 0.93 0.94 1842
165
 
166
+ micro avg 0.90 0.91 0.91 5942
167
+ macro avg 0.89 0.90 0.90 5942
168
+ weighted avg 0.90 0.91 0.91 5942
169
  |
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+ | 0.0285 | 2.6681 | 5000 | 0.0770 | 0.9823 | 0.9143 | 0.9157 | 0.9150 | precision recall f1-score support
171
 
172
+ LOC 0.93 0.94 0.94 1837
173
+ MISC 0.89 0.83 0.86 922
174
  ORG 0.86 0.87 0.87 1341
175
+ PER 0.94 0.97 0.95 1842
176
 
177
+ micro avg 0.91 0.92 0.91 5942
178
+ macro avg 0.91 0.90 0.90 5942
179
+ weighted avg 0.91 0.92 0.91 5942
180
  |
181
+ | 0.0256 | 2.9349 | 5500 | 0.0779 | 0.9840 | 0.9260 | 0.9244 | 0.9252 | precision recall f1-score support
182
 
183
+ LOC 0.94 0.95 0.94 1837
184
+ MISC 0.89 0.86 0.87 922
185
+ ORG 0.90 0.87 0.89 1341
186
+ PER 0.95 0.97 0.96 1842
187
 
188
+ micro avg 0.93 0.92 0.93 5942
189
+ macro avg 0.92 0.91 0.92 5942
190
+ weighted avg 0.93 0.92 0.92 5942
191
  |
192
+ | 0.0135 | 3.2017 | 6000 | 0.0878 | 0.9831 | 0.9111 | 0.9229 | 0.9170 | precision recall f1-score support
193
 
194
+ LOC 0.93 0.95 0.94 1837
195
+ MISC 0.82 0.87 0.84 922
196
+ ORG 0.89 0.86 0.87 1341
197
  PER 0.95 0.97 0.96 1842
198
 
199
+ micro avg 0.91 0.92 0.92 5942
200
+ macro avg 0.90 0.91 0.90 5942
201
+ weighted avg 0.91 0.92 0.92 5942
202
  |
203
+ | 0.0112 | 3.4685 | 6500 | 0.0845 | 0.9835 | 0.9131 | 0.9265 | 0.9197 | precision recall f1-score support
204
 
205
+ LOC 0.93 0.96 0.94 1837
206
+ MISC 0.85 0.88 0.86 922
207
+ ORG 0.87 0.88 0.87 1341
208
+ PER 0.96 0.96 0.96 1842
209
 
210
+ micro avg 0.91 0.93 0.92 5942
211
+ macro avg 0.90 0.92 0.91 5942
212
+ weighted avg 0.91 0.93 0.92 5942
213
  |
214
+ | 0.0119 | 3.7353 | 7000 | 0.0901 | 0.9837 | 0.9230 | 0.9219 | 0.9225 | precision recall f1-score support
215
 
216
  LOC 0.94 0.96 0.95 1837
217
+ MISC 0.90 0.83 0.86 922
218
+ ORG 0.88 0.88 0.88 1341
219
  PER 0.95 0.96 0.96 1842
220
 
221
+ micro avg 0.92 0.92 0.92 5942
222
  macro avg 0.92 0.91 0.91 5942
223
+ weighted avg 0.92 0.92 0.92 5942
224
  |
225
+ | 0.0132 | 4.0021 | 7500 | 0.0902 | 0.9843 | 0.9262 | 0.9248 | 0.9255 | precision recall f1-score support
226
 
227
+ LOC 0.93 0.96 0.95 1837
228
+ MISC 0.89 0.86 0.87 922
229
+ ORG 0.91 0.87 0.89 1341
230
  PER 0.95 0.96 0.96 1842
231
 
232
+ micro avg 0.93 0.92 0.93 5942
233
+ macro avg 0.92 0.91 0.92 5942
234
+ weighted avg 0.93 0.92 0.93 5942
235
+ |
236
+ | 0.006 | 4.2689 | 8000 | 0.0914 | 0.9844 | 0.9233 | 0.9273 | 0.9253 | precision recall f1-score support
237
+
238
+ LOC 0.94 0.96 0.95 1837
239
+ MISC 0.88 0.86 0.87 922
240
+ ORG 0.88 0.89 0.88 1341
241
+ PER 0.96 0.96 0.96 1842
242
+
243
  micro avg 0.92 0.93 0.93 5942
244
  macro avg 0.92 0.92 0.92 5942
245
  weighted avg 0.92 0.93 0.93 5942
246
  |
247
+ | 0.005 | 4.5358 | 8500 | 0.0919 | 0.9846 | 0.9284 | 0.9268 | 0.9276 | precision recall f1-score support
248
+
249
+ LOC 0.95 0.96 0.95 1837
250
+ MISC 0.90 0.85 0.87 922
251
+ ORG 0.90 0.88 0.89 1341
252
+ PER 0.95 0.97 0.96 1842
253
+
254
+ micro avg 0.93 0.93 0.93 5942
255
+ macro avg 0.92 0.91 0.92 5942
256
+ weighted avg 0.93 0.93 0.93 5942
257
+ |
258
+ | 0.0062 | 4.8026 | 9000 | 0.0887 | 0.9845 | 0.9232 | 0.9286 | 0.9259 | precision recall f1-score support
259
 
260
  LOC 0.94 0.96 0.95 1837
261
+ MISC 0.87 0.87 0.87 922
262
+ ORG 0.89 0.88 0.89 1341
263
+ PER 0.95 0.96 0.96 1842
264
 
265
+ micro avg 0.92 0.93 0.93 5942
266
+ macro avg 0.91 0.92 0.92 5942
267
+ weighted avg 0.92 0.93 0.93 5942
268
  |
269
 
270
 
271
  ### Framework versions
272
 
273
  - Transformers 4.47.1
274
+ - Pytorch 2.5.1+cpu
275
  - Datasets 3.2.0
276
  - Tokenizers 0.21.0
model.safetensors CHANGED
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- oid sha256:8fa4c6574f4c5c8e77faec469deb4f23621c74fc650c296b45b9400e31070c57
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  size 435617620
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:165e72e887066034c0e8b42aa5da40b8eecf0035af54db60ea150c7221090277
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  size 435617620