acharya-jyu commited on
Commit
b409066
·
verified ·
1 Parent(s): 899199e

Upload best model

Browse files
Files changed (3) hide show
  1. README.md +199 -0
  2. config.json +623 -0
  3. model.safetensors +3 -0
README.md ADDED
@@ -0,0 +1,199 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags: []
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+ This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
config.json ADDED
@@ -0,0 +1,623 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "cambridgeltl/SapBERT-from-PubMedBERT-fulltext",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "dropout_rate": 0.5,
9
+ "gradient_checkpointing": false,
10
+ "hidden_act": "gelu",
11
+ "hidden_dropout_prob": 0.1,
12
+ "hidden_size": 768,
13
+ "initializer_range": 0.02,
14
+ "intermediate_size": 3072,
15
+ "layer_norm_eps": 1e-12,
16
+ "max_position_embeddings": 512,
17
+ "metrics": {
18
+ "epoch": 2,
19
+ "train_loss": 0.0051190271463160105,
20
+ "train_metrics": {
21
+ "class_0": {
22
+ "f1": 1.0,
23
+ "precision": 1.0,
24
+ "recall": 1.0,
25
+ "support": 454
26
+ },
27
+ "class_1": {
28
+ "f1": 0.9988998899889989,
29
+ "precision": 0.9978021978021978,
30
+ "recall": 1.0,
31
+ "support": 454
32
+ },
33
+ "class_10": {
34
+ "f1": 1.0,
35
+ "precision": 1.0,
36
+ "recall": 1.0,
37
+ "support": 454
38
+ },
39
+ "class_11": {
40
+ "f1": 1.0,
41
+ "precision": 1.0,
42
+ "recall": 1.0,
43
+ "support": 454
44
+ },
45
+ "class_12": {
46
+ "f1": 0.8571428571428571,
47
+ "precision": 1.0,
48
+ "recall": 0.75,
49
+ "support": 8
50
+ },
51
+ "class_13": {
52
+ "f1": 1.0,
53
+ "precision": 1.0,
54
+ "recall": 1.0,
55
+ "support": 454
56
+ },
57
+ "class_14": {
58
+ "f1": 0.9988998899889989,
59
+ "precision": 0.9978021978021978,
60
+ "recall": 1.0,
61
+ "support": 454
62
+ },
63
+ "class_15": {
64
+ "f1": 1.0,
65
+ "precision": 1.0,
66
+ "recall": 1.0,
67
+ "support": 454
68
+ },
69
+ "class_16": {
70
+ "f1": 0.9619151251360174,
71
+ "precision": 0.9505376344086022,
72
+ "recall": 0.973568281938326,
73
+ "support": 454
74
+ },
75
+ "class_17": {
76
+ "f1": 1.0,
77
+ "precision": 1.0,
78
+ "recall": 1.0,
79
+ "support": 454
80
+ },
81
+ "class_18": {
82
+ "f1": 0.9978021978021978,
83
+ "precision": 0.9956140350877193,
84
+ "recall": 1.0,
85
+ "support": 454
86
+ },
87
+ "class_19": {
88
+ "f1": 0.0,
89
+ "precision": 0.0,
90
+ "recall": 0.0,
91
+ "support": 8
92
+ },
93
+ "class_2": {
94
+ "f1": 0.9988998899889989,
95
+ "precision": 0.9978021978021978,
96
+ "recall": 1.0,
97
+ "support": 454
98
+ },
99
+ "class_20": {
100
+ "f1": 1.0,
101
+ "precision": 1.0,
102
+ "recall": 1.0,
103
+ "support": 454
104
+ },
105
+ "class_21": {
106
+ "f1": 1.0,
107
+ "precision": 1.0,
108
+ "recall": 1.0,
109
+ "support": 454
110
+ },
111
+ "class_22": {
112
+ "f1": 0.9988998899889989,
113
+ "precision": 0.9978021978021978,
114
+ "recall": 1.0,
115
+ "support": 454
116
+ },
117
+ "class_23": {
118
+ "f1": 1.0,
119
+ "precision": 1.0,
120
+ "recall": 1.0,
121
+ "support": 454
122
+ },
123
+ "class_24": {
124
+ "f1": 1.0,
125
+ "precision": 1.0,
126
+ "recall": 1.0,
127
+ "support": 454
128
+ },
129
+ "class_25": {
130
+ "f1": 1.0,
131
+ "precision": 1.0,
132
+ "recall": 1.0,
133
+ "support": 454
134
+ },
135
+ "class_26": {
136
+ "f1": 1.0,
137
+ "precision": 1.0,
138
+ "recall": 1.0,
139
+ "support": 454
140
+ },
141
+ "class_27": {
142
+ "f1": 1.0,
143
+ "precision": 1.0,
144
+ "recall": 1.0,
145
+ "support": 454
146
+ },
147
+ "class_28": {
148
+ "f1": 0.9988998899889989,
149
+ "precision": 0.9978021978021978,
150
+ "recall": 1.0,
151
+ "support": 454
152
+ },
153
+ "class_29": {
154
+ "f1": 1.0,
155
+ "precision": 1.0,
156
+ "recall": 1.0,
157
+ "support": 454
158
+ },
159
+ "class_3": {
160
+ "f1": 1.0,
161
+ "precision": 1.0,
162
+ "recall": 1.0,
163
+ "support": 454
164
+ },
165
+ "class_30": {
166
+ "f1": 1.0,
167
+ "precision": 1.0,
168
+ "recall": 1.0,
169
+ "support": 454
170
+ },
171
+ "class_31": {
172
+ "f1": 1.0,
173
+ "precision": 1.0,
174
+ "recall": 1.0,
175
+ "support": 454
176
+ },
177
+ "class_32": {
178
+ "f1": 1.0,
179
+ "precision": 1.0,
180
+ "recall": 1.0,
181
+ "support": 454
182
+ },
183
+ "class_33": {
184
+ "f1": 1.0,
185
+ "precision": 1.0,
186
+ "recall": 1.0,
187
+ "support": 454
188
+ },
189
+ "class_34": {
190
+ "f1": 1.0,
191
+ "precision": 1.0,
192
+ "recall": 1.0,
193
+ "support": 454
194
+ },
195
+ "class_35": {
196
+ "f1": 1.0,
197
+ "precision": 1.0,
198
+ "recall": 1.0,
199
+ "support": 454
200
+ },
201
+ "class_36": {
202
+ "f1": 0.9988998899889989,
203
+ "precision": 0.9978021978021978,
204
+ "recall": 1.0,
205
+ "support": 454
206
+ },
207
+ "class_37": {
208
+ "f1": 1.0,
209
+ "precision": 1.0,
210
+ "recall": 1.0,
211
+ "support": 454
212
+ },
213
+ "class_38": {
214
+ "f1": 1.0,
215
+ "precision": 1.0,
216
+ "recall": 1.0,
217
+ "support": 454
218
+ },
219
+ "class_39": {
220
+ "f1": 1.0,
221
+ "precision": 1.0,
222
+ "recall": 1.0,
223
+ "support": 454
224
+ },
225
+ "class_4": {
226
+ "f1": 1.0,
227
+ "precision": 1.0,
228
+ "recall": 1.0,
229
+ "support": 454
230
+ },
231
+ "class_40": {
232
+ "f1": 1.0,
233
+ "precision": 1.0,
234
+ "recall": 1.0,
235
+ "support": 454
236
+ },
237
+ "class_41": {
238
+ "f1": 1.0,
239
+ "precision": 1.0,
240
+ "recall": 1.0,
241
+ "support": 454
242
+ },
243
+ "class_42": {
244
+ "f1": 1.0,
245
+ "precision": 1.0,
246
+ "recall": 1.0,
247
+ "support": 454
248
+ },
249
+ "class_43": {
250
+ "f1": 0.9988998899889989,
251
+ "precision": 0.9978021978021978,
252
+ "recall": 1.0,
253
+ "support": 454
254
+ },
255
+ "class_44": {
256
+ "f1": 0.9988998899889989,
257
+ "precision": 0.9978021978021978,
258
+ "recall": 1.0,
259
+ "support": 454
260
+ },
261
+ "class_45": {
262
+ "f1": 1.0,
263
+ "precision": 1.0,
264
+ "recall": 1.0,
265
+ "support": 454
266
+ },
267
+ "class_46": {
268
+ "f1": 0.9988974641675854,
269
+ "precision": 1.0,
270
+ "recall": 0.9977973568281938,
271
+ "support": 454
272
+ },
273
+ "class_47": {
274
+ "f1": 1.0,
275
+ "precision": 1.0,
276
+ "recall": 1.0,
277
+ "support": 454
278
+ },
279
+ "class_48": {
280
+ "f1": 1.0,
281
+ "precision": 1.0,
282
+ "recall": 1.0,
283
+ "support": 454
284
+ },
285
+ "class_5": {
286
+ "f1": 0.9609810479375697,
287
+ "precision": 0.9729119638826185,
288
+ "recall": 0.9493392070484582,
289
+ "support": 454
290
+ },
291
+ "class_6": {
292
+ "f1": 0.9988998899889989,
293
+ "precision": 0.9978021978021978,
294
+ "recall": 1.0,
295
+ "support": 454
296
+ },
297
+ "class_7": {
298
+ "f1": 1.0,
299
+ "precision": 1.0,
300
+ "recall": 1.0,
301
+ "support": 454
302
+ },
303
+ "class_8": {
304
+ "f1": 1.0,
305
+ "precision": 1.0,
306
+ "recall": 1.0,
307
+ "support": 454
308
+ },
309
+ "class_9": {
310
+ "f1": 1.0,
311
+ "precision": 1.0,
312
+ "recall": 1.0,
313
+ "support": 454
314
+ },
315
+ "weighted": {
316
+ "f1": 0.9976518967154577,
317
+ "precision": 0.9974840624601394,
318
+ "recall": 0.9978458368455558
319
+ }
320
+ },
321
+ "val_loss": 2.0530410248135764,
322
+ "val_metrics": {
323
+ "class_0": {
324
+ "f1": 1.0,
325
+ "precision": 1.0,
326
+ "recall": 1.0,
327
+ "support": 30
328
+ },
329
+ "class_1": {
330
+ "f1": 1.0,
331
+ "precision": 1.0,
332
+ "recall": 1.0,
333
+ "support": 50
334
+ },
335
+ "class_10": {
336
+ "f1": 0.875,
337
+ "precision": 0.875,
338
+ "recall": 0.875,
339
+ "support": 24
340
+ },
341
+ "class_11": {
342
+ "f1": 1.0,
343
+ "precision": 1.0,
344
+ "recall": 1.0,
345
+ "support": 39
346
+ },
347
+ "class_12": {
348
+ "f1": 0.968421052631579,
349
+ "precision": 0.9387755102040817,
350
+ "recall": 1.0,
351
+ "support": 46
352
+ },
353
+ "class_13": {
354
+ "f1": 1.0,
355
+ "precision": 1.0,
356
+ "recall": 1.0,
357
+ "support": 36
358
+ },
359
+ "class_14": {
360
+ "f1": 0.75,
361
+ "precision": 0.72,
362
+ "recall": 0.782608695652174,
363
+ "support": 23
364
+ },
365
+ "class_15": {
366
+ "f1": 0.684931506849315,
367
+ "precision": 0.8620689655172413,
368
+ "recall": 0.5681818181818182,
369
+ "support": 44
370
+ },
371
+ "class_16": {
372
+ "f1": 0.896551724137931,
373
+ "precision": 0.8125,
374
+ "recall": 1.0,
375
+ "support": 39
376
+ },
377
+ "class_17": {
378
+ "f1": 1.0,
379
+ "precision": 1.0,
380
+ "recall": 1.0,
381
+ "support": 9
382
+ },
383
+ "class_18": {
384
+ "f1": 0.8,
385
+ "precision": 0.717948717948718,
386
+ "recall": 0.9032258064516129,
387
+ "support": 31
388
+ },
389
+ "class_19": {
390
+ "f1": 0.8952380952380953,
391
+ "precision": 0.9215686274509803,
392
+ "recall": 0.8703703703703703,
393
+ "support": 54
394
+ },
395
+ "class_2": {
396
+ "f1": 0.865979381443299,
397
+ "precision": 0.9545454545454546,
398
+ "recall": 0.7924528301886793,
399
+ "support": 53
400
+ },
401
+ "class_20": {
402
+ "f1": 1.0,
403
+ "precision": 1.0,
404
+ "recall": 1.0,
405
+ "support": 39
406
+ },
407
+ "class_21": {
408
+ "f1": 0.2077922077922078,
409
+ "precision": 0.27586206896551724,
410
+ "recall": 0.16666666666666666,
411
+ "support": 48
412
+ },
413
+ "class_22": {
414
+ "f1": 0.15384615384615385,
415
+ "precision": 0.45454545454545453,
416
+ "recall": 0.09259259259259259,
417
+ "support": 54
418
+ },
419
+ "class_23": {
420
+ "f1": 0.5901639344262295,
421
+ "precision": 0.6666666666666666,
422
+ "recall": 0.5294117647058824,
423
+ "support": 34
424
+ },
425
+ "class_24": {
426
+ "f1": 1.0,
427
+ "precision": 1.0,
428
+ "recall": 1.0,
429
+ "support": 41
430
+ },
431
+ "class_25": {
432
+ "f1": 0.95,
433
+ "precision": 0.95,
434
+ "recall": 0.95,
435
+ "support": 60
436
+ },
437
+ "class_26": {
438
+ "f1": 1.0,
439
+ "precision": 1.0,
440
+ "recall": 1.0,
441
+ "support": 43
442
+ },
443
+ "class_27": {
444
+ "f1": 0.972972972972973,
445
+ "precision": 0.9473684210526315,
446
+ "recall": 1.0,
447
+ "support": 18
448
+ },
449
+ "class_28": {
450
+ "f1": 0.8372093023255814,
451
+ "precision": 0.7346938775510204,
452
+ "recall": 0.972972972972973,
453
+ "support": 37
454
+ },
455
+ "class_29": {
456
+ "f1": 0.8461538461538461,
457
+ "precision": 1.0,
458
+ "recall": 0.7333333333333333,
459
+ "support": 30
460
+ },
461
+ "class_3": {
462
+ "f1": 0.6902654867256637,
463
+ "precision": 0.527027027027027,
464
+ "recall": 1.0,
465
+ "support": 39
466
+ },
467
+ "class_30": {
468
+ "f1": 0.49122807017543857,
469
+ "precision": 1.0,
470
+ "recall": 0.32558139534883723,
471
+ "support": 43
472
+ },
473
+ "class_31": {
474
+ "f1": 0.8636363636363636,
475
+ "precision": 0.76,
476
+ "recall": 1.0,
477
+ "support": 38
478
+ },
479
+ "class_32": {
480
+ "f1": 0.038461538461538464,
481
+ "precision": 1.0,
482
+ "recall": 0.0196078431372549,
483
+ "support": 51
484
+ },
485
+ "class_33": {
486
+ "f1": 0.8314606741573034,
487
+ "precision": 0.7254901960784313,
488
+ "recall": 0.9736842105263158,
489
+ "support": 38
490
+ },
491
+ "class_34": {
492
+ "f1": 0.9105691056910569,
493
+ "precision": 0.875,
494
+ "recall": 0.9491525423728814,
495
+ "support": 59
496
+ },
497
+ "class_35": {
498
+ "f1": 0.6842105263157895,
499
+ "precision": 0.5306122448979592,
500
+ "recall": 0.9629629629629629,
501
+ "support": 27
502
+ },
503
+ "class_36": {
504
+ "f1": 0.38461538461538464,
505
+ "precision": 1.0,
506
+ "recall": 0.23809523809523808,
507
+ "support": 21
508
+ },
509
+ "class_37": {
510
+ "f1": 0.44,
511
+ "precision": 1.0,
512
+ "recall": 0.28205128205128205,
513
+ "support": 39
514
+ },
515
+ "class_38": {
516
+ "f1": 1.0,
517
+ "precision": 1.0,
518
+ "recall": 1.0,
519
+ "support": 32
520
+ },
521
+ "class_39": {
522
+ "f1": 0.9122807017543859,
523
+ "precision": 0.8387096774193549,
524
+ "recall": 1.0,
525
+ "support": 26
526
+ },
527
+ "class_4": {
528
+ "f1": 0.8421052631578947,
529
+ "precision": 1.0,
530
+ "recall": 0.7272727272727273,
531
+ "support": 44
532
+ },
533
+ "class_40": {
534
+ "f1": 0.5185185185185185,
535
+ "precision": 0.5833333333333334,
536
+ "recall": 0.4666666666666667,
537
+ "support": 15
538
+ },
539
+ "class_41": {
540
+ "f1": 0.8,
541
+ "precision": 0.6666666666666666,
542
+ "recall": 1.0,
543
+ "support": 26
544
+ },
545
+ "class_42": {
546
+ "f1": 1.0,
547
+ "precision": 1.0,
548
+ "recall": 1.0,
549
+ "support": 31
550
+ },
551
+ "class_43": {
552
+ "f1": 0.6707317073170732,
553
+ "precision": 0.5045871559633027,
554
+ "recall": 1.0,
555
+ "support": 110
556
+ },
557
+ "class_44": {
558
+ "f1": 0.8470588235294118,
559
+ "precision": 0.8372093023255814,
560
+ "recall": 0.8571428571428571,
561
+ "support": 42
562
+ },
563
+ "class_45": {
564
+ "f1": 0.896,
565
+ "precision": 0.8115942028985508,
566
+ "recall": 1.0,
567
+ "support": 112
568
+ },
569
+ "class_46": {
570
+ "f1": 1.0,
571
+ "precision": 1.0,
572
+ "recall": 1.0,
573
+ "support": 11
574
+ },
575
+ "class_5": {
576
+ "f1": 0.7755102040816326,
577
+ "precision": 0.7037037037037037,
578
+ "recall": 0.8636363636363636,
579
+ "support": 22
580
+ },
581
+ "class_6": {
582
+ "f1": 1.0,
583
+ "precision": 1.0,
584
+ "recall": 1.0,
585
+ "support": 86
586
+ },
587
+ "class_7": {
588
+ "f1": 0.3188405797101449,
589
+ "precision": 0.6470588235294118,
590
+ "recall": 0.21153846153846154,
591
+ "support": 52
592
+ },
593
+ "class_8": {
594
+ "f1": 0.927536231884058,
595
+ "precision": 0.9411764705882353,
596
+ "recall": 0.9142857142857143,
597
+ "support": 105
598
+ },
599
+ "class_9": {
600
+ "f1": 1.0,
601
+ "precision": 1.0,
602
+ "recall": 1.0,
603
+ "support": 49
604
+ },
605
+ "weighted": {
606
+ "f1": 0.7870526389291528,
607
+ "precision": 0.8395130170555933,
608
+ "recall": 0.814
609
+ }
610
+ }
611
+ },
612
+ "model_type": "bert",
613
+ "num_attention_heads": 12,
614
+ "num_classes": 49,
615
+ "num_hidden_layers": 12,
616
+ "pad_token_id": 0,
617
+ "position_embedding_type": "absolute",
618
+ "torch_dtype": "float32",
619
+ "transformers_version": "4.47.1",
620
+ "type_vocab_size": 2,
621
+ "use_cache": true,
622
+ "vocab_size": 30522
623
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:762d1973200333163bc9c2a4fa2907e8168f95e1809e7f72f903439a433b1dcc
3
+ size 437951328