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tmwstw7
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spanmarker-bert-base-cased-custom-small

Token Classification
SpanMarker
TensorBoard
Safetensors
ner
named-entity-recognition
generated_from_span_marker_trainer
Eval Results (legacy)
Model card Files
xet
 Metrics Community
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macpaw-research/mnemos_entity_extractor_v1_small

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Files changed (19) hide show
  1. README.md +62 -60
  2. config.json +79 -79
  3. model.safetensors +1 -1
  4. runs/Nov05_18-00-40_21820ec588a1/events.out.tfevents.1762365675.21820ec588a1.374.0 +3 -0
  5. runs/Nov05_18-00-40_21820ec588a1/events.out.tfevents.1762366113.21820ec588a1.374.1 +3 -0
  6. runs/Nov05_18-23-52_21820ec588a1/events.out.tfevents.1762367074.21820ec588a1.374.2 +3 -0
  7. runs/Nov05_18-23-52_21820ec588a1/events.out.tfevents.1762367470.21820ec588a1.374.3 +3 -0
  8. runs/Nov06_16-09-04_9857a63c5837/events.out.tfevents.1762445386.9857a63c5837.5460.0 +3 -0
  9. runs/Nov06_16-09-04_9857a63c5837/events.out.tfevents.1762445965.9857a63c5837.5460.1 +3 -0
  10. runs/Oct21_19-47-14_c090c1c7e874/events.out.tfevents.1761076072.c090c1c7e874.4195.0 +3 -0
  11. runs/Oct21_19-47-14_c090c1c7e874/events.out.tfevents.1761076439.c090c1c7e874.4195.1 +3 -0
  12. runs/Oct21_20-14-14_c090c1c7e874/events.out.tfevents.1761077692.c090c1c7e874.4195.2 +3 -0
  13. runs/Oct21_20-14-14_c090c1c7e874/events.out.tfevents.1761078080.c090c1c7e874.4195.3 +3 -0
  14. runs/Oct21_20-22-17_c090c1c7e874/events.out.tfevents.1761078175.c090c1c7e874.4195.4 +3 -0
  15. runs/Oct21_20-22-17_c090c1c7e874/events.out.tfevents.1761078577.c090c1c7e874.4195.5 +3 -0
  16. runs/Oct21_20-36-54_c090c1c7e874/events.out.tfevents.1761079052.c090c1c7e874.17733.0 +3 -0
  17. runs/Oct21_20-36-54_c090c1c7e874/events.out.tfevents.1761079414.c090c1c7e874.17733.1 +3 -0
  18. tokenizer_config.json +1 -1
  19. training_args.bin +1 -1
README.md CHANGED
@@ -6,16 +6,18 @@ tags:
6
  - named-entity-recognition
7
  - generated_from_span_marker_trainer
8
  widget:
9
- - text: Please lower the brightness, locate any images exceeding 2 MB that contain
10
- the summary section, and activate privacy settings in the application.
11
- - text: Before the meeting in Room 204, can you copy the references list from the
12
- thesis and disable notifications for comments in Google Docs?
13
- - text: For tomorrow' s Parent - Teacher Conference at Lincoln High School, make sure
14
- the volume is set to low and email the agenda to principal @ lincolnhs . edu.
15
- - text: Is the conclusion on page 12 of the thesis . pdf ready for review by Marcus
16
- Osei this Thursday? Also, please check if auto - save is enabled.
17
- - text: Upload the image called vacation2023 . png to my boss via his work email and
18
- delete all photos from the gallery app.
 
 
19
  pipeline_tag: token-classification
20
  library_name: span-marker
21
  metrics:
@@ -34,13 +36,13 @@ model-index:
34
  split: eval
35
  metrics:
36
  - type: f1
37
- value: 0.8599876058665565
38
  name: F1
39
  - type: precision
40
- value: 0.8455601592330815
41
  name: Precision
42
  - type: recall
43
- value: 0.874915938130464
44
  name: Recall
45
  ---
46
 
@@ -54,7 +56,7 @@ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that ca
54
  - **Model Type:** SpanMarker
55
  <!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
56
  - **Maximum Sequence Length:** 512 tokens
57
- - **Maximum Entity Length:** 8 words
58
  <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
59
  <!-- - **Language:** Unknown -->
60
  <!-- - **License:** Unknown -->
@@ -65,51 +67,51 @@ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that ca
65
  - **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
66
 
67
  ### Model Labels
68
- | Label | Examples |
69
- |:---------------|:----------------------------------------------------------------|
70
- | action | "arrive", "print", "bring" |
71
- | app_data_type | "posts", "playlists", "messages" |
72
- | app_name | "Notion", "Spotify", "Viber" |
73
- | app_setting | "notifications", "dark mode", "language setting" |
74
- | contact_info | "address", "email address", "office number" |
75
- | date | "March 3rd", "15 . 04 . 2024", "2024 - 04 - 01" |
76
- | device_setting | "notifications", "screen timeout", "bluetooth" |
77
- | event_title | "table", "Board Meeting", "Charity Gala" |
78
- | file_name | "sales_data . xlsx", "vacation_photos . zip", "expenses . xlsx" |
79
- | file_size | "above 700MB", "above 500 kb", "2 MB" |
80
- | file_type | "document files", "spreadsheet", "videos" |
81
- | folder_name | "Downloads", "Budget Reports", "Invoices" |
82
- | in_file_data | "table of contents", "table 2", "table 4" |
83
- | location | "conference room", "Riverside Pavilion", "San Francisco office" |
84
- | person_name | "Maria Lopez", "Priya Singh", "Alexei Petrov" |
85
- | relationship | "friend", "sister", "colleague" |
86
- | system_command | "airplane mode", "enable", "delete" |
87
- | time | "13 : 45", "8 : 30 AM", "noon" |
88
 
89
  ## Evaluation
90
 
91
  ### Metrics
92
  | Label | Precision | Recall | F1 |
93
  |:---------------|:----------|:-------|:-------|
94
- | **all** | 0.8456 | 0.8749 | 0.8600 |
95
- | action | 0.8261 | 0.9137 | 0.8677 |
96
- | app_data_type | 0.7631 | 0.6862 | 0.7226 |
97
- | app_name | 0.9066 | 0.9407 | 0.9233 |
98
- | app_setting | 0.8525 | 0.8998 | 0.8755 |
99
- | contact_info | 0.8847 | 0.9089 | 0.8966 |
100
- | date | 0.9342 | 0.9302 | 0.9322 |
101
- | device_setting | 0.8345 | 0.8450 | 0.8397 |
102
- | event_title | 0.8881 | 0.9149 | 0.9013 |
103
- | file_name | 0.9393 | 0.9243 | 0.9317 |
104
- | file_size | 0.7518 | 0.7357 | 0.7437 |
105
- | file_type | 0.7535 | 0.8697 | 0.8075 |
106
- | folder_name | 0.9523 | 0.9106 | 0.9310 |
107
- | in_file_data | 0.7632 | 0.7969 | 0.7797 |
108
- | location | 0.8953 | 0.8658 | 0.8803 |
109
- | person_name | 0.9742 | 0.9788 | 0.9765 |
110
- | relationship | 0.9381 | 0.9476 | 0.9428 |
111
- | system_command | 0.75 | 0.7491 | 0.7495 |
112
- | time | 0.8733 | 0.8385 | 0.8555 |
113
 
114
  ## Uses
115
 
@@ -121,7 +123,7 @@ from span_marker import SpanMarkerModel
121
  # Download from the 🤗 Hub
122
  model = SpanMarkerModel.from_pretrained("span_marker_model_id")
123
  # Run inference
124
- entities = model.predict("Upload the image called vacation2023 . png to my boss via his work email and delete all photos from the gallery app.")
125
  ```
126
 
127
  ### Downstream Use
@@ -172,8 +174,8 @@ trainer.save_model("span_marker_model_id-finetuned")
172
  ### Training Set Metrics
173
  | Training set | Min | Median | Max |
174
  |:----------------------|:----|:--------|:----|
175
- | Sentence length | 5 | 19.3422 | 54 |
176
- | Entities per sentence | 2 | 5.9111 | 13 |
177
 
178
  ### Training Hyperparameters
179
  - learning_rate: 5e-05
@@ -183,17 +185,17 @@ trainer.save_model("span_marker_model_id-finetuned")
183
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
184
  - lr_scheduler_type: linear
185
  - lr_scheduler_warmup_ratio: 0.1
186
- - num_epochs: 4
187
  - mixed_precision_training: Native AMP
188
 
189
  ### Training Results
190
  | Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
191
  |:------:|:----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
192
- | 1.9763 | 1000 | 0.0369 | 0.8426 | 0.8649 | 0.8536 | 0.9231 |
193
- | 3.9526 | 2000 | 0.0352 | 0.8450 | 0.8751 | 0.8598 | 0.9264 |
194
 
195
  ### Framework Versions
196
- - Python: 3.12.11
197
  - SpanMarker: 1.7.0
198
  - Transformers: 4.51.3
199
  - PyTorch: 2.8.0+cu126
 
6
  - named-entity-recognition
7
  - generated_from_span_marker_trainer
8
  widget:
9
+ - text: On 07 Nov, send my brother the summary from section 2 of the document and
10
+ enable airplane mode on my phone
11
+ - text: Could you please share the' Budget Reports' folder with me and update the
12
+ notification settings in Slack before the Quarterly Review Meeting? Also, send
13
+ the details to my email at emily . chen @ workmail . com
14
+ - text: Find all images from March 3rd that are less than 1MB, and read out the caption
15
+ under figure 5 . Set the device to silent mode
16
+ - text: Please send the document named annual_report_2023 . xlsx from the Finance
17
+ folder, specifically the summary on page 5, to my manager at manager @ acme .
18
+ com
19
+ - text: Text my mother at + 44 7911 123456 the summary from paragraph 4, and then
20
+ enable bluetooth
21
  pipeline_tag: token-classification
22
  library_name: span-marker
23
  metrics:
 
36
  split: eval
37
  metrics:
38
  - type: f1
39
+ value: 0.8683998712169995
40
  name: F1
41
  - type: precision
42
+ value: 0.8558622877994606
43
  name: Precision
44
  - type: recall
45
+ value: 0.8813102434242771
46
  name: Recall
47
  ---
48
 
 
56
  - **Model Type:** SpanMarker
57
  <!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
58
  - **Maximum Sequence Length:** 512 tokens
59
+ - **Maximum Entity Length:** 12 words
60
  <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
61
  <!-- - **Language:** Unknown -->
62
  <!-- - **License:** Unknown -->
 
67
  - **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
68
 
69
  ### Model Labels
70
+ | Label | Examples |
71
+ |:---------------|:--------------------------------------------------------------------------------|
72
+ | action | "Remind", "scheduled", "review" |
73
+ | app_data_type | "items", "images", "videos" |
74
+ | app_name | "Camera", "phone", "Slack" |
75
+ | contact_info | "sarah . lee @ company . org", "123 Maple Street , Springfield", "home address" |
76
+ | date | "20 . 10 . 1999", "before", "January 18 - June 15" |
77
+ | event_title | "team sync", "Marketing Strategy Meeting", "Budget Planning" |
78
+ | file_name | "notes", "budget_overview . xlsx", "project_plan . docx" |
79
+ | file_size | "under 500 kb", "smaller than 50 kb", "exceeding 100 mb" |
80
+ | file_type | "documents", "document", "image" |
81
+ | folder_name | "Projects", "Work", "Photos" |
82
+ | in_file_data | "appendix section", "page 10", "section 5" |
83
+ | limits | "top 8", "all", "every" |
84
+ | location | "Room 204", "server room", "library" |
85
+ | person_name | "Jonathan Kim", "Mr . Osei", "Lucas Müller" |
86
+ | relationship | "manager", "brother", "cousin" |
87
+ | setting | "brightness", "airplane mode", "notifications" |
88
+ | system_command | "disable", "move", "switch on" |
89
+ | time | "9 : 00 AM", "10 : 45", "10 : 00 AM" |
90
 
91
  ## Evaluation
92
 
93
  ### Metrics
94
  | Label | Precision | Recall | F1 |
95
  |:---------------|:----------|:-------|:-------|
96
+ | **all** | 0.8559 | 0.8813 | 0.8684 |
97
+ | action | 0.8173 | 0.9245 | 0.8676 |
98
+ | app_data_type | 0.7960 | 0.6828 | 0.7351 |
99
+ | app_name | 0.9432 | 0.9432 | 0.9432 |
100
+ | contact_info | 0.8722 | 0.9091 | 0.8903 |
101
+ | date | 0.9160 | 0.8993 | 0.9076 |
102
+ | event_title | 0.8659 | 0.9107 | 0.8877 |
103
+ | file_name | 0.9371 | 0.9280 | 0.9326 |
104
+ | file_size | 0.7810 | 0.7810 | 0.7810 |
105
+ | file_type | 0.7731 | 0.8786 | 0.8225 |
106
+ | folder_name | 0.9618 | 0.8968 | 0.9282 |
107
+ | in_file_data | 0.7486 | 0.7867 | 0.7672 |
108
+ | limits | 0.9048 | 0.6786 | 0.7755 |
109
+ | location | 0.8917 | 0.8571 | 0.8741 |
110
+ | person_name | 0.9885 | 0.9885 | 0.9885 |
111
+ | relationship | 0.9505 | 0.9541 | 0.9523 |
112
+ | setting | 0.8974 | 0.9255 | 0.9112 |
113
+ | system_command | 0.7889 | 0.7441 | 0.7659 |
114
+ | time | 0.9076 | 0.8587 | 0.8825 |
115
 
116
  ## Uses
117
 
 
123
  # Download from the 🤗 Hub
124
  model = SpanMarkerModel.from_pretrained("span_marker_model_id")
125
  # Run inference
126
+ entities = model.predict("Text my mother at + 44 7911 123456 the summary from paragraph 4, and then enable bluetooth")
127
  ```
128
 
129
  ### Downstream Use
 
174
  ### Training Set Metrics
175
  | Training set | Min | Median | Max |
176
  |:----------------------|:----|:--------|:----|
177
+ | Sentence length | 3 | 19.0206 | 53 |
178
+ | Entities per sentence | 1 | 5.7015 | 13 |
179
 
180
  ### Training Hyperparameters
181
  - learning_rate: 5e-05
 
185
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
186
  - lr_scheduler_type: linear
187
  - lr_scheduler_warmup_ratio: 0.1
188
+ - num_epochs: 5
189
  - mixed_precision_training: Native AMP
190
 
191
  ### Training Results
192
  | Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
193
  |:------:|:----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
194
+ | 1.8553 | 1000 | 0.0344 | 0.8301 | 0.8650 | 0.8472 | 0.9204 |
195
+ | 3.7106 | 2000 | 0.0271 | 0.8524 | 0.8804 | 0.8662 | 0.9316 |
196
 
197
  ### Framework Versions
198
+ - Python: 3.12.12
199
  - SpanMarker: 1.7.0
200
  - Transformers: 4.51.3
201
  - PyTorch: 2.8.0+cu126
config.json CHANGED
@@ -35,37 +35,37 @@
35
  "1": "B-action",
36
  "2": "B-app_data_type",
37
  "3": "B-app_name",
38
- "4": "B-app_setting",
39
- "5": "B-contact_info",
40
- "6": "B-date",
41
- "7": "B-device_setting",
42
- "8": "B-event_title",
43
- "9": "B-file_name",
44
- "10": "B-file_size",
45
- "11": "B-file_type",
46
- "12": "B-folder_name",
47
- "13": "B-in_file_data",
48
- "14": "B-location",
49
- "15": "B-person_name",
50
- "16": "B-relationship",
51
  "17": "B-system_command",
52
  "18": "B-time",
53
  "19": "I-action",
54
  "20": "I-app_data_type",
55
  "21": "I-app_name",
56
- "22": "I-app_setting",
57
- "23": "I-contact_info",
58
- "24": "I-date",
59
- "25": "I-device_setting",
60
- "26": "I-event_title",
61
- "27": "I-file_name",
62
- "28": "I-file_size",
63
- "29": "I-file_type",
64
- "30": "I-folder_name",
65
- "31": "I-in_file_data",
66
- "32": "I-location",
67
- "33": "I-person_name",
68
- "34": "I-relationship",
69
  "35": "I-system_command",
70
  "36": "I-time"
71
  },
@@ -77,37 +77,37 @@
77
  "B-action": 1,
78
  "B-app_data_type": 2,
79
  "B-app_name": 3,
80
- "B-app_setting": 4,
81
- "B-contact_info": 5,
82
- "B-date": 6,
83
- "B-device_setting": 7,
84
- "B-event_title": 8,
85
- "B-file_name": 9,
86
- "B-file_size": 10,
87
- "B-file_type": 11,
88
- "B-folder_name": 12,
89
- "B-in_file_data": 13,
90
- "B-location": 14,
91
- "B-person_name": 15,
92
- "B-relationship": 16,
93
  "B-system_command": 17,
94
  "B-time": 18,
95
  "I-action": 19,
96
  "I-app_data_type": 20,
97
  "I-app_name": 21,
98
- "I-app_setting": 22,
99
- "I-contact_info": 23,
100
- "I-date": 24,
101
- "I-device_setting": 25,
102
- "I-event_title": 26,
103
- "I-file_name": 27,
104
- "I-file_size": 28,
105
- "I-file_type": 29,
106
- "I-folder_name": 30,
107
- "I-in_file_data": 31,
108
- "I-location": 32,
109
- "I-person_name": 33,
110
- "I-relationship": 34,
111
  "I-system_command": 35,
112
  "I-time": 36,
113
  "O": 0
@@ -155,25 +155,25 @@
155
  "use_cache": true,
156
  "vocab_size": 29000
157
  },
158
- "entity_max_length": 8,
159
  "id2label": {
160
  "0": "O",
161
  "1": "action",
162
  "2": "app_data_type",
163
  "3": "app_name",
164
- "4": "app_setting",
165
- "5": "contact_info",
166
- "6": "date",
167
- "7": "device_setting",
168
- "8": "event_title",
169
- "9": "file_name",
170
- "10": "file_size",
171
- "11": "file_type",
172
- "12": "folder_name",
173
- "13": "in_file_data",
174
- "14": "location",
175
- "15": "person_name",
176
- "16": "relationship",
177
  "17": "system_command",
178
  "18": "time"
179
  },
@@ -221,19 +221,19 @@
221
  "action": 1,
222
  "app_data_type": 2,
223
  "app_name": 3,
224
- "app_setting": 4,
225
- "contact_info": 5,
226
- "date": 6,
227
- "device_setting": 7,
228
- "event_title": 8,
229
- "file_name": 9,
230
- "file_size": 10,
231
- "file_type": 11,
232
- "folder_name": 12,
233
- "in_file_data": 13,
234
- "location": 14,
235
- "person_name": 15,
236
- "relationship": 16,
237
  "system_command": 17,
238
  "time": 18
239
  },
 
35
  "1": "B-action",
36
  "2": "B-app_data_type",
37
  "3": "B-app_name",
38
+ "4": "B-contact_info",
39
+ "5": "B-date",
40
+ "6": "B-event_title",
41
+ "7": "B-file_name",
42
+ "8": "B-file_size",
43
+ "9": "B-file_type",
44
+ "10": "B-folder_name",
45
+ "11": "B-in_file_data",
46
+ "12": "B-limits",
47
+ "13": "B-location",
48
+ "14": "B-person_name",
49
+ "15": "B-relationship",
50
+ "16": "B-setting",
51
  "17": "B-system_command",
52
  "18": "B-time",
53
  "19": "I-action",
54
  "20": "I-app_data_type",
55
  "21": "I-app_name",
56
+ "22": "I-contact_info",
57
+ "23": "I-date",
58
+ "24": "I-event_title",
59
+ "25": "I-file_name",
60
+ "26": "I-file_size",
61
+ "27": "I-file_type",
62
+ "28": "I-folder_name",
63
+ "29": "I-in_file_data",
64
+ "30": "I-limits",
65
+ "31": "I-location",
66
+ "32": "I-person_name",
67
+ "33": "I-relationship",
68
+ "34": "I-setting",
69
  "35": "I-system_command",
70
  "36": "I-time"
71
  },
 
77
  "B-action": 1,
78
  "B-app_data_type": 2,
79
  "B-app_name": 3,
80
+ "B-contact_info": 4,
81
+ "B-date": 5,
82
+ "B-event_title": 6,
83
+ "B-file_name": 7,
84
+ "B-file_size": 8,
85
+ "B-file_type": 9,
86
+ "B-folder_name": 10,
87
+ "B-in_file_data": 11,
88
+ "B-limits": 12,
89
+ "B-location": 13,
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