Hugging Face's logo

RinaChen
/
GuWen-all-mpnet-base-v2

Safetensors
Model card Files Community
RinaChen commited on
Commit
8297c2d
•
1 Parent(s): db4fc81

Upload 11 files

Browse files
Files changed (11) hide show
  1. final/1_Pooling/config.json +10 -0
  2. final/README.md +858 -0
  3. final/config.json +24 -0
  4. final/config_sentence_transformers.json +10 -0
  5. final/model.safetensors +3 -0
  6. final/modules.json +20 -0
  7. final/sentence_bert_config.json +4 -0
  8. final/special_tokens_map.json +51 -0
  9. final/tokenizer.json +0 -0
  10. final/tokenizer_config.json +72 -0
  11. final/vocab.txt +0 -0
final/1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "word_embedding_dimension": 768,
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
+ }
final/README.md ADDED
@@ -0,0 +1,858 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: sentence-transformers/all-mpnet-base-v2
3
+ datasets: []
4
+ language: []
5
+ library_name: sentence-transformers
6
+ pipeline_tag: sentence-similarity
7
+ tags:
8
+ - sentence-transformers
9
+ - sentence-similarity
10
+ - feature-extraction
11
+ - generated_from_trainer
12
+ - dataset_size:756057
13
+ - loss:MultipleNegativesRankingLoss
14
+ widget:
15
+ - source_sentence: 府君奈何以盖世之才欲立忠于垂亡之国
16
+ sentences:
17
+ - 将远方进贡来的奇兽飞禽以及白山鸡等物纵还山林比起雍畤的祭祀礼数颇有增加
18
+ - 您为什么以盖绝当世的奇才却打算向这个面临灭亡的国家尽效忠心呢
19
+ - 大统年间他出任岐州刺史在任不久就因为能力强而闻名
20
+ - source_sentence: 将率既至授单于印绂诏令上故印绂
21
+ sentences:
22
+ - 已经到达的五威将到达后授给单于新印信宣读诏书要求交回汉朝旧印信
23
+ - 于是拜陶隗为西南面招讨使
24
+ - 司马错建议秦惠王攻打蜀国张仪说 还不如进攻韩国
25
+ - source_sentence: 行醮礼皇太子诣醴席乐作
26
+ sentences:
27
+ - 闰七月十七日上宣宗废除皇后胡氏尊谥
28
+ - 等到看见西羌鼠窃狗盗父不父子不子君臣没有分别四夷之人西羌最为低下
29
+ - 行醮礼皇太子来到酒醴席奏乐
30
+ - source_sentence: 领军臧盾太府卿沈僧果等并被时遇孝绰尤轻之
31
+ sentences:
32
+ - 过了几天太宰官又来要国书并且说 我国自太宰府以东上国使臣没有到过今大朝派使臣来若不见国书何以相信
33
+ - 所以丹阳葛洪解释说浑天仪注说 天体像鸡蛋地就像是鸡蛋中的蛋黄独处于天体之内天是大的而地是小的
34
+ - 领军臧盾太府卿沈僧果等都是因赶上时机而得到官职的孝绰尤其轻蔑他们每次在朝中集合会面虽然一起做官但从不与他们说话
35
+ - source_sentence: 九月辛未太祖曾孙舒国公从式进封安定郡王
36
+ sentences:
37
+ - 九月初二太祖曾孙舒国公从式进封安定郡王
38
+ - 杨难当在汉中大肆烧杀抢劫然后率众离开了汉中向西返回仇池留下赵温据守梁州又派他的魏兴太守薛健屯驻黄金山
39
+ - 正统元年普定蛮夷阿迟等反叛非法称王四处出击攻打掠夺
40
+ ---
41
+
42
+ # SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
43
+
44
+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
45
+
46
+ ## Model Details
47
+
48
+ ### Model Description
49
+ - **Model Type:** Sentence Transformer
50
+ - **Base model:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 84f2bcc00d77236f9e89c8a360a00fb1139bf47d -->
51
+ - **Maximum Sequence Length:** 384 tokens
52
+ - **Output Dimensionality:** 768 tokens
53
+ - **Similarity Function:** Cosine Similarity
54
+ <!-- - **Training Dataset:** Unknown -->
55
+ <!-- - **Language:** Unknown -->
56
+ <!-- - **License:** Unknown -->
57
+
58
+ ### Model Sources
59
+
60
+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
61
+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
62
+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
63
+
64
+ ### Full Model Architecture
65
+
66
+ ```
67
+ SentenceTransformer(
68
+ (0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel
69
+ (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
70
+ (2): Normalize()
71
+ )
72
+ ```
73
+
74
+ ## Usage
75
+
76
+ ### Direct Usage (Sentence Transformers)
77
+
78
+ First install the Sentence Transformers library:
79
+
80
+ ```bash
81
+ pip install -U sentence-transformers
82
+ ```
83
+
84
+ Then you can load this model and run inference.
85
+ ```python
86
+ from sentence_transformers import SentenceTransformer
87
+
88
+ # Download from the 🤗 Hub
89
+ model = SentenceTransformer("sentence_transformers_model_id")
90
+ # Run inference
91
+ sentences = [
92
+ '九月辛未太祖曾孙舒国公从式进封安定郡王',
93
+ '九月初二太祖曾孙舒国公从式进封安定郡王',
94
+ '杨难当在汉中大肆烧杀抢劫然后率众离开了汉中向西返回仇池留下赵温据守梁州又派他的魏兴太守薛健屯驻黄金山',
95
+ ]
96
+ embeddings = model.encode(sentences)
97
+ print(embeddings.shape)
98
+ # [3, 768]
99
+
100
+ # Get the similarity scores for the embeddings
101
+ similarities = model.similarity(embeddings, embeddings)
102
+ print(similarities.shape)
103
+ # [3, 3]
104
+ ```
105
+
106
+ <!--
107
+ ### Direct Usage (Transformers)
108
+
109
+ <details><summary>Click to see the direct usage in Transformers</summary>
110
+
111
+ </details>
112
+ -->
113
+
114
+ <!--
115
+ ### Downstream Usage (Sentence Transformers)
116
+
117
+ You can finetune this model on your own dataset.
118
+
119
+ <details><summary>Click to expand</summary>
120
+
121
+ </details>
122
+ -->
123
+
124
+ <!--
125
+ ### Out-of-Scope Use
126
+
127
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
128
+ -->
129
+
130
+ <!--
131
+ ## Bias, Risks and Limitations
132
+
133
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
134
+ -->
135
+
136
+ <!--
137
+ ### Recommendations
138
+
139
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
140
+ -->
141
+
142
+ ## Training Details
143
+
144
+ ### Training Dataset
145
+
146
+ #### Unnamed Dataset
147
+
148
+
149
+ * Size: 756,057 training samples
150
+ * Columns: <code>anchor</code> and <code>positive</code>
151
+ * Approximate statistics based on the first 1000 samples:
152
+ | | anchor | positive |
153
+ |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
154
+ | type | string | string |
155
+ | details | <ul><li>min: 4 tokens</li><li>mean: 20.76 tokens</li><li>max: 199 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 31.27 tokens</li><li>max: 384 tokens</li></ul> |
156
+ * Samples:
157
+ | anchor | positive |
158
+ |:------------------------------------------|:------------------------------------------------------------|
159
+ | <code>虏怀兼弱之威挟广地之计强兵大众亲自凌殄旍鼓弥年矢石不息</code> | <code>魏人怀有兼并弱小的威严胸藏拓展土地的计谋强人的军队亲自出征侵逼消灭旌旗战鼓连年出动战事不停息</code> |
160
+ | <code>孟子曰 以善服人者未有能服人者也以善养人然后能服天下</code> | <code>孟子说 用自己的善良使人们服从的人没有能使人服从的用善良影响教导人们才能使天下的人们都信服</code> |
161
+ | <code>开庆初大元兵渡江理宗议迁都平江庆元后谏不可恐摇动民心乃止</code> | <code>开庆初年大元朝部队渡过长江理宗打算迁都到平江庆元皇后劝谏不可迁都深恐动摇民心理宗才作罢</code> |
162
+ * Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
163
+ ```json
164
+ {
165
+ "scale": 20.0,
166
+ "similarity_fct": "cos_sim"
167
+ }
168
+ ```
169
+
170
+ ### Evaluation Dataset
171
+
172
+ #### Unnamed Dataset
173
+
174
+
175
+ * Size: 84,007 evaluation samples
176
+ * Columns: <code>anchor</code> and <code>positive</code>
177
+ * Approximate statistics based on the first 1000 samples:
178
+ | | anchor | positive |
179
+ |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
180
+ | type | string | string |
181
+ | details | <ul><li>min: 4 tokens</li><li>mean: 20.23 tokens</li><li>max: 138 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 31.42 tokens</li><li>max: 384 tokens</li></ul> |
182
+ * Samples:
183
+ | anchor | positive |
184
+ |:--------------------------------------------------|:------------------------------------------------------------------|
185
+ | <code>雒阳户五万二千八百三十九</code> | <code>雒阳有五万二千八百三十九户</code> |
186
+ | <code>拜南青州刺史在任有政绩</code> | <code>任南青州刺史很有政绩</code> |
187
+ | <code>第六品以下加不得服金钅奠绫锦锦绣七缘绮貂豽裘金叉环铒及以金校饰器物张绛帐</code> | <code>官位在第六品以下的官员再增加不得穿用金钿绫锦锦绣七缘绮貂钠皮衣金叉缳饵以及用金装饰的器物张绛帐等衣服物品</code> |
188
+ * Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
189
+ ```json
190
+ {
191
+ "scale": 20.0,
192
+ "similarity_fct": "cos_sim"
193
+ }
194
+ ```
195
+
196
+ ### Training Hyperparameters
197
+ #### Non-Default Hyperparameters
198
+
199
+ - `eval_strategy`: steps
200
+ - `per_device_train_batch_size`: 16
201
+ - `per_device_eval_batch_size`: 16
202
+ - `num_train_epochs`: 1
203
+ - `warmup_ratio`: 0.1
204
+ - `fp16`: True
205
+ - `load_best_model_at_end`: True
206
+ - `batch_sampler`: no_duplicates
207
+
208
+ #### All Hyperparameters
209
+ <details><summary>Click to expand</summary>
210
+
211
+ - `overwrite_output_dir`: False
212
+ - `do_predict`: False
213
+ - `eval_strategy`: steps
214
+ - `prediction_loss_only`: True
215
+ - `per_device_train_batch_size`: 16
216
+ - `per_device_eval_batch_size`: 16
217
+ - `per_gpu_train_batch_size`: None
218
+ - `per_gpu_eval_batch_size`: None
219
+ - `gradient_accumulation_steps`: 1
220
+ - `eval_accumulation_steps`: None
221
+ - `learning_rate`: 5e-05
222
+ - `weight_decay`: 0.0
223
+ - `adam_beta1`: 0.9
224
+ - `adam_beta2`: 0.999
225
+ - `adam_epsilon`: 1e-08
226
+ - `max_grad_norm`: 1.0
227
+ - `num_train_epochs`: 1
228
+ - `max_steps`: -1
229
+ - `lr_scheduler_type`: linear
230
+ - `lr_scheduler_kwargs`: {}
231
+ - `warmup_ratio`: 0.1
232
+ - `warmup_steps`: 0
233
+ - `log_level`: passive
234
+ - `log_level_replica`: warning
235
+ - `log_on_each_node`: True
236
+ - `logging_nan_inf_filter`: True
237
+ - `save_safetensors`: True
238
+ - `save_on_each_node`: False
239
+ - `save_only_model`: False
240
+ - `restore_callback_states_from_checkpoint`: False
241
+ - `no_cuda`: False
242
+ - `use_cpu`: False
243
+ - `use_mps_device`: False
244
+ - `seed`: 42
245
+ - `data_seed`: None
246
+ - `jit_mode_eval`: False
247
+ - `use_ipex`: False
248
+ - `bf16`: False
249
+ - `fp16`: True
250
+ - `fp16_opt_level`: O1
251
+ - `half_precision_backend`: auto
252
+ - `bf16_full_eval`: False
253
+ - `fp16_full_eval`: False
254
+ - `tf32`: None
255
+ - `local_rank`: 0
256
+ - `ddp_backend`: None
257
+ - `tpu_num_cores`: None
258
+ - `tpu_metrics_debug`: False
259
+ - `debug`: []
260
+ - `dataloader_drop_last`: False
261
+ - `dataloader_num_workers`: 0
262
+ - `dataloader_prefetch_factor`: None
263
+ - `past_index`: -1
264
+ - `disable_tqdm`: False
265
+ - `remove_unused_columns`: True
266
+ - `label_names`: None
267
+ - `load_best_model_at_end`: True
268
+ - `ignore_data_skip`: False
269
+ - `fsdp`: []
270
+ - `fsdp_min_num_params`: 0
271
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
272
+ - `fsdp_transformer_layer_cls_to_wrap`: None
273
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
274
+ - `deepspeed`: None
275
+ - `label_smoothing_factor`: 0.0
276
+ - `optim`: adamw_torch
277
+ - `optim_args`: None
278
+ - `adafactor`: False
279
+ - `group_by_length`: False
280
+ - `length_column_name`: length
281
+ - `ddp_find_unused_parameters`: None
282
+ - `ddp_bucket_cap_mb`: None
283
+ - `ddp_broadcast_buffers`: False
284
+ - `dataloader_pin_memory`: True
285
+ - `dataloader_persistent_workers`: False
286
+ - `skip_memory_metrics`: True
287
+ - `use_legacy_prediction_loop`: False
288
+ - `push_to_hub`: False
289
+ - `resume_from_checkpoint`: None
290
+ - `hub_model_id`: None
291
+ - `hub_strategy`: every_save
292
+ - `hub_private_repo`: False
293
+ - `hub_always_push`: False
294
+ - `gradient_checkpointing`: False
295
+ - `gradient_checkpointing_kwargs`: None
296
+ - `include_inputs_for_metrics`: False
297
+ - `eval_do_concat_batches`: True
298
+ - `fp16_backend`: auto
299
+ - `push_to_hub_model_id`: None
300
+ - `push_to_hub_organization`: None
301
+ - `mp_parameters`:
302
+ - `auto_find_batch_size`: False
303
+ - `full_determinism`: False
304
+ - `torchdynamo`: None
305
+ - `ray_scope`: last
306
+ - `ddp_timeout`: 1800
307
+ - `torch_compile`: False
308
+ - `torch_compile_backend`: None
309
+ - `torch_compile_mode`: None
310
+ - `dispatch_batches`: None
311
+ - `split_batches`: None
312
+ - `include_tokens_per_second`: False
313
+ - `include_num_input_tokens_seen`: False
314
+ - `neftune_noise_alpha`: None
315
+ - `optim_target_modules`: None
316
+ - `batch_eval_metrics`: False
317
+ - `eval_on_start`: False
318
+ - `batch_sampler`: no_duplicates
319
+ - `multi_dataset_batch_sampler`: proportional
320
+
321
+ </details>
322
+
323
+ ### Training Logs
324
+ <details><summary>Click to expand</summary>
325
+
326
+ | Epoch | Step | Training Loss | loss |
327
+ |:----------:|:---------:|:-------------:|:--------:|
328
+ | 0.0021 | 100 | 0.6475 | - |
329
+ | 0.0042 | 200 | 0.5193 | - |
330
+ | 0.0063 | 300 | 0.4132 | - |
331
+ | 0.0085 | 400 | 0.3981 | - |
332
+ | 0.0106 | 500 | 0.4032 | - |
333
+ | 0.0127 | 600 | 0.3627 | - |
334
+ | 0.0148 | 700 | 0.3821 | - |
335
+ | 0.0169 | 800 | 0.3767 | - |
336
+ | 0.0190 | 900 | 0.3731 | - |
337
+ | 0.0212 | 1000 | 0.3744 | - |
338
+ | 0.0233 | 1100 | 0.3115 | - |
339
+ | 0.0254 | 1200 | 0.3998 | - |
340
+ | 0.0275 | 1300 | 0.3103 | - |
341
+ | 0.0296 | 1400 | 0.3251 | - |
342
+ | 0.0317 | 1500 | 0.2833 | - |
343
+ | 0.0339 | 1600 | 0.3335 | - |
344
+ | 0.0360 | 1700 | 0.3281 | - |
345
+ | 0.0381 | 1800 | 0.423 | - |
346
+ | 0.0402 | 1900 | 0.3687 | - |
347
+ | 0.0423 | 2000 | 0.3452 | - |
348
+ | 0.0444 | 2100 | 0.8643 | - |
349
+ | 0.0466 | 2200 | 0.4279 | - |
350
+ | 0.0487 | 2300 | 0.4188 | - |
351
+ | 0.0508 | 2400 | 0.3676 | - |
352
+ | 0.0529 | 2500 | 0.3279 | - |
353
+ | 0.0550 | 2600 | 0.3415 | - |
354
+ | 0.0571 | 2700 | 1.5834 | - |
355
+ | 0.0593 | 2800 | 2.7778 | - |
356
+ | 0.0614 | 2900 | 2.7734 | - |
357
+ | 0.0635 | 3000 | 2.7732 | - |
358
+ | 0.0656 | 3100 | 2.7751 | - |
359
+ | 0.0677 | 3200 | 2.7731 | - |
360
+ | 0.0698 | 3300 | 2.773 | - |
361
+ | 0.0720 | 3400 | 2.7727 | - |
362
+ | 0.0741 | 3500 | 2.7534 | - |
363
+ | 0.0762 | 3600 | 2.2219 | - |
364
+ | 0.0783 | 3700 | 0.5137 | - |
365
+ | 0.0804 | 3800 | 0.4143 | - |
366
+ | 0.0825 | 3900 | 0.4002 | - |
367
+ | 0.0846 | 4000 | 0.368 | - |
368
+ | 0.0868 | 4100 | 0.3879 | - |
369
+ | 0.0889 | 4200 | 0.3519 | - |
370
+ | 0.0910 | 4300 | 0.364 | - |
371
+ | 0.0931 | 4400 | 0.3618 | - |
372
+ | 0.0952 | 4500 | 0.3545 | - |
373
+ | 0.0973 | 4600 | 0.379 | - |
374
+ | 0.0995 | 4700 | 0.3837 | - |
375
+ | 0.1016 | 4800 | 0.3553 | - |
376
+ | 0.1037 | 4900 | 0.3519 | - |
377
+ | 0.1058 | 5000 | 0.3416 | 0.3487 |
378
+ | 0.1079 | 5100 | 0.3763 | - |
379
+ | 0.1100 | 5200 | 0.3748 | - |
380
+ | 0.1122 | 5300 | 0.3564 | - |
381
+ | 0.1143 | 5400 | 0.336 | - |
382
+ | 0.1164 | 5500 | 0.3601 | - |
383
+ | 0.1185 | 5600 | 0.3521 | - |
384
+ | 0.1206 | 5700 | 0.376 | - |
385
+ | 0.1227 | 5800 | 0.3011 | - |
386
+ | 0.1249 | 5900 | 0.345 | - |
387
+ | 0.1270 | 6000 | 0.3211 | - |
388
+ | 0.1291 | 6100 | 0.3673 | - |
389
+ | 0.1312 | 6200 | 0.3762 | - |
390
+ | 0.1333 | 6300 | 0.3562 | - |
391
+ | 0.1354 | 6400 | 0.2761 | - |
392
+ | 0.1376 | 6500 | 0.3186 | - |
393
+ | 0.1397 | 6600 | 0.3582 | - |
394
+ | 0.1418 | 6700 | 0.3454 | - |
395
+ | 0.1439 | 6800 | 0.3429 | - |
396
+ | 0.1460 | 6900 | 0.2932 | - |
397
+ | 0.1481 | 7000 | 0.3357 | - |
398
+ | 0.1503 | 7100 | 0.2979 | - |
399
+ | 0.1524 | 7200 | 0.313 | - |
400
+ | 0.1545 | 7300 | 0.3364 | - |
401
+ | 0.1566 | 7400 | 0.3459 | - |
402
+ | 0.1587 | 7500 | 0.279 | - |
403
+ | 0.1608 | 7600 | 0.3274 | - |
404
+ | 0.1629 | 7700 | 0.3367 | - |
405
+ | 0.1651 | 7800 | 0.2935 | - |
406
+ | 0.1672 | 7900 | 0.3415 | - |
407
+ | 0.1693 | 8000 | 0.2838 | - |
408
+ | 0.1714 | 8100 | 0.2667 | - |
409
+ | 0.1735 | 8200 | 0.3051 | - |
410
+ | 0.1756 | 8300 | 0.3197 | - |
411
+ | 0.1778 | 8400 | 0.3086 | - |
412
+ | 0.1799 | 8500 | 0.3186 | - |
413
+ | 0.1820 | 8600 | 0.3063 | - |
414
+ | 0.1841 | 8700 | 0.2967 | - |
415
+ | 0.1862 | 8800 | 0.3069 | - |
416
+ | 0.1883 | 8900 | 0.3391 | - |
417
+ | 0.1905 | 9000 | 0.335 | - |
418
+ | 0.1926 | 9100 | 0.3115 | - |
419
+ | 0.1947 | 9200 | 0.3214 | - |
420
+ | 0.1968 | 9300 | 0.278 | - |
421
+ | 0.1989 | 9400 | 0.2833 | - |
422
+ | 0.2010 | 9500 | 0.303 | - |
423
+ | 0.2032 | 9600 | 0.3238 | - |
424
+ | 0.2053 | 9700 | 0.2622 | - |
425
+ | 0.2074 | 9800 | 0.3295 | - |
426
+ | 0.2095 | 9900 | 0.2699 | - |
427
+ | 0.2116 | 10000 | 0.2426 | 0.2962 |
428
+ | 0.2137 | 10100 | 0.262 | - |
429
+ | 0.2159 | 10200 | 0.3199 | - |
430
+ | 0.2180 | 10300 | 0.3677 | - |
431
+ | 0.2201 | 10400 | 0.2423 | - |
432
+ | 0.2222 | 10500 | 0.3446 | - |
433
+ | 0.2243 | 10600 | 0.3002 | - |
434
+ | 0.2264 | 10700 | 0.2863 | - |
435
+ | 0.2286 | 10800 | 0.2692 | - |
436
+ | 0.2307 | 10900 | 0.3157 | - |
437
+ | 0.2328 | 11000 | 0.3172 | - |
438
+ | 0.2349 | 11100 | 0.3622 | - |
439
+ | 0.2370 | 11200 | 0.3019 | - |
440
+ | 0.2391 | 11300 | 0.2789 | - |
441
+ | 0.2412 | 11400 | 0.2872 | - |
442
+ | 0.2434 | 11500 | 0.2823 | - |
443
+ | 0.2455 | 11600 | 0.3017 | - |
444
+ | 0.2476 | 11700 | 0.2573 | - |
445
+ | 0.2497 | 11800 | 0.3104 | - |
446
+ | 0.2518 | 11900 | 0.2857 | - |
447
+ | 0.2539 | 12000 | 0.2898 | - |
448
+ | 0.2561 | 12100 | 0.2389 | - |
449
+ | 0.2582 | 12200 | 0.3137 | - |
450
+ | 0.2603 | 12300 | 0.3029 | - |
451
+ | 0.2624 | 12400 | 0.2894 | - |
452
+ | 0.2645 | 12500 | 0.2665 | - |
453
+ | 0.2666 | 12600 | 0.2705 | - |
454
+ | 0.2688 | 12700 | 0.2673 | - |
455
+ | 0.2709 | 12800 | 0.248 | - |
456
+ | 0.2730 | 12900 | 0.2417 | - |
457
+ | 0.2751 | 13000 | 0.2852 | - |
458
+ | 0.2772 | 13100 | 0.2619 | - |
459
+ | 0.2793 | 13200 | 0.3157 | - |
460
+ | 0.2815 | 13300 | 0.2464 | - |
461
+ | 0.2836 | 13400 | 0.2837 | - |
462
+ | 0.2857 | 13500 | 0.3202 | - |
463
+ | 0.2878 | 13600 | 0.2618 | - |
464
+ | 0.2899 | 13700 | 0.2823 | - |
465
+ | 0.2920 | 13800 | 0.2634 | - |
466
+ | 0.2942 | 13900 | 0.2747 | - |
467
+ | 0.2963 | 14000 | 0.2835 | - |
468
+ | 0.2984 | 14100 | 0.2594 | - |
469
+ | 0.3005 | 14200 | 0.2744 | - |
470
+ | 0.3026 | 14300 | 0.2722 | - |
471
+ | 0.3047 | 14400 | 0.2514 | - |
472
+ | 0.3069 | 14500 | 0.2809 | - |
473
+ | 0.3090 | 14600 | 0.2949 | - |
474
+ | 0.3111 | 14700 | 0.2687 | - |
475
+ | 0.3132 | 14800 | 0.3 | - |
476
+ | 0.3153 | 14900 | 0.2684 | - |
477
+ | 0.3174 | 15000 | 0.2894 | 0.2790 |
478
+ | 0.3195 | 15100 | 0.2676 | - |
479
+ | 0.3217 | 15200 | 0.2519 | - |
480
+ | 0.3238 | 15300 | 0.2698 | - |
481
+ | 0.3259 | 15400 | 0.2898 | - |
482
+ | 0.3280 | 15500 | 0.2359 | - |
483
+ | 0.3301 | 15600 | 0.2866 | - |
484
+ | 0.3322 | 15700 | 0.3098 | - |
485
+ | 0.3344 | 15800 | 0.2809 | - |
486
+ | 0.3365 | 15900 | 0.3081 | - |
487
+ | 0.3386 | 16000 | 0.266 | - |
488
+ | 0.3407 | 16100 | 0.2523 | - |
489
+ | 0.3428 | 16200 | 0.3215 | - |
490
+ | 0.3449 | 16300 | 0.2883 | - |
491
+ | 0.3471 | 16400 | 0.2897 | - |
492
+ | 0.3492 | 16500 | 0.3174 | - |
493
+ | 0.3513 | 16600 | 0.2878 | - |
494
+ | 0.3534 | 16700 | 0.267 | - |
495
+ | 0.3555 | 16800 | 0.2452 | - |
496
+ | 0.3576 | 16900 | 0.2429 | - |
497
+ | 0.3598 | 17000 | 0.2178 | - |
498
+ | 0.3619 | 17100 | 0.2798 | - |
499
+ | 0.3640 | 17200 | 0.2367 | - |
500
+ | 0.3661 | 17300 | 0.2554 | - |
501
+ | 0.3682 | 17400 | 0.2883 | - |
502
+ | 0.3703 | 17500 | 0.2567 | - |
503
+ | 0.3725 | 17600 | 0.27 | - |
504
+ | 0.3746 | 17700 | 0.2837 | - |
505
+ | 0.3767 | 17800 | 0.2783 | - |
506
+ | 0.3788 | 17900 | 0.2517 | - |
507
+ | 0.3809 | 18000 | 0.2545 | - |
508
+ | 0.3830 | 18100 | 0.2632 | - |
509
+ | 0.3852 | 18200 | 0.2074 | - |
510
+ | 0.3873 | 18300 | 0.2276 | - |
511
+ | 0.3894 | 18400 | 0.3022 | - |
512
+ | 0.3915 | 18500 | 0.2381 | - |
513
+ | 0.3936 | 18600 | 0.2552 | - |
514
+ | 0.3957 | 18700 | 0.2579 | - |
515
+ | 0.3978 | 18800 | 0.2655 | - |
516
+ | 0.4000 | 18900 | 0.252 | - |
517
+ | 0.4021 | 19000 | 0.2876 | - |
518
+ | 0.4042 | 19100 | 0.2037 | - |
519
+ | 0.4063 | 19200 | 0.251 | - |
520
+ | 0.4084 | 19300 | 0.2588 | - |
521
+ | 0.4105 | 19400 | 0.201 | - |
522
+ | 0.4127 | 19500 | 0.2828 | - |
523
+ | 0.4148 | 19600 | 0.2637 | - |
524
+ | 0.4169 | 19700 | 0.3233 | - |
525
+ | 0.4190 | 19800 | 0.2475 | - |
526
+ | 0.4211 | 19900 | 0.2618 | - |
527
+ | 0.4232 | 20000 | 0.3272 | 0.2519 |
528
+ | 0.4254 | 20100 | 0.3074 | - |
529
+ | 0.4275 | 20200 | 0.2994 | - |
530
+ | 0.4296 | 20300 | 0.2624 | - |
531
+ | 0.4317 | 20400 | 0.2389 | - |
532
+ | 0.4338 | 20500 | 0.2809 | - |
533
+ | 0.4359 | 20600 | 0.2659 | - |
534
+ | 0.4381 | 20700 | 0.2508 | - |
535
+ | 0.4402 | 20800 | 0.2542 | - |
536
+ | 0.4423 | 20900 | 0.2525 | - |
537
+ | 0.4444 | 21000 | 0.257 | - |
538
+ | 0.4465 | 21100 | 0.2242 | - |
539
+ | 0.4486 | 21200 | 0.2307 | - |
540
+ | 0.4508 | 21300 | 0.2721 | - |
541
+ | 0.4529 | 21400 | 0.2489 | - |
542
+ | 0.4550 | 21500 | 0.2933 | - |
543
+ | 0.4571 | 21600 | 0.2448 | - |
544
+ | 0.4592 | 21700 | 0.2619 | - |
545
+ | 0.4613 | 21800 | 0.2488 | - |
546
+ | 0.4635 | 21900 | 0.2411 | - |
547
+ | 0.4656 | 22000 | 0.2964 | - |
548
+ | 0.4677 | 22100 | 0.2062 | - |
549
+ | 0.4698 | 22200 | 0.2665 | - |
550
+ | 0.4719 | 22300 | 0.263 | - |
551
+ | 0.4740 | 22400 | 0.2418 | - |
552
+ | 0.4762 | 22500 | 0.2879 | - |
553
+ | 0.4783 | 22600 | 0.2406 | - |
554
+ | 0.4804 | 22700 | 0.2448 | - |
555
+ | 0.4825 | 22800 | 0.243 | - |
556
+ | 0.4846 | 22900 | 0.2863 | - |
557
+ | 0.4867 | 23000 | 0.2833 | - |
558
+ | 0.4888 | 23100 | 0.2784 | - |
559
+ | 0.4910 | 23200 | 0.2789 | - |
560
+ | 0.4931 | 23300 | 0.2495 | - |
561
+ | 0.4952 | 23400 | 0.2872 | - |
562
+ | 0.4973 | 23500 | 0.2487 | - |
563
+ | 0.4994 | 23600 | 0.2669 | - |
564
+ | 0.5015 | 23700 | 0.2748 | - |
565
+ | 0.5037 | 23800 | 0.246 | - |
566
+ | 0.5058 | 23900 | 0.2512 | - |
567
+ | 0.5079 | 24000 | 0.222 | - |
568
+ | 0.5100 | 24100 | 0.2662 | - |
569
+ | 0.5121 | 24200 | 0.2238 | - |
570
+ | 0.5142 | 24300 | 0.2399 | - |
571
+ | 0.5164 | 24400 | 0.2595 | - |
572
+ | 0.5185 | 24500 | 0.3002 | - |
573
+ | 0.5206 | 24600 | 0.2553 | - |
574
+ | 0.5227 | 24700 | 0.226 | - |
575
+ | 0.5248 | 24800 | 0.2823 | - |
576
+ | 0.5269 | 24900 | 0.2737 | - |
577
+ | 0.5291 | 25000 | 0.2237 | 0.2492 |
578
+ | 0.5312 | 25100 | 0.2642 | - |
579
+ | 0.5333 | 25200 | 0.2486 | - |
580
+ | 0.5354 | 25300 | 0.2527 | - |
581
+ | 0.5375 | 25400 | 0.2363 | - |
582
+ | 0.5396 | 25500 | 0.2443 | - |
583
+ | 0.5418 | 25600 | 0.2485 | - |
584
+ | 0.5439 | 25700 | 0.2434 | - |
585
+ | 0.5460 | 25800 | 0.2631 | - |
586
+ | 0.5481 | 25900 | 0.284 | - |
587
+ | 0.5502 | 26000 | 0.217 | - |
588
+ | 0.5523 | 26100 | 0.2246 | - |
589
+ | 0.5545 | 26200 | 0.2614 | - |
590
+ | 0.5566 | 26300 | 0.2722 | - |
591
+ | 0.5587 | 26400 | 0.2114 | - |
592
+ | 0.5608 | 26500 | 0.2623 | - |
593
+ | 0.5629 | 26600 | 0.2475 | - |
594
+ | 0.5650 | 26700 | 0.2449 | - |
595
+ | 0.5671 | 26800 | 0.2423 | - |
596
+ | 0.5693 | 26900 | 0.2435 | - |
597
+ | 0.5714 | 27000 | 0.2446 | - |
598
+ | 0.5735 | 27100 | 0.2248 | - |
599
+ | 0.5756 | 27200 | 0.2159 | - |
600
+ | 0.5777 | 27300 | 0.2415 | - |
601
+ | 0.5798 | 27400 | 0.2257 | - |
602
+ | 0.5820 | 27500 | 0.2775 | - |
603
+ | 0.5841 | 27600 | 0.2533 | - |
604
+ | 0.5862 | 27700 | 0.2893 | - |
605
+ | 0.5883 | 27800 | 0.2095 | - |
606
+ | 0.5904 | 27900 | 0.2156 | - |
607
+ | 0.5925 | 28000 | 0.2315 | - |
608
+ | 0.5947 | 28100 | 0.2865 | - |
609
+ | 0.5968 | 28200 | 0.262 | - |
610
+ | 0.5989 | 28300 | 0.2506 | - |
611
+ | 0.6010 | 28400 | 0.2472 | - |
612
+ | 0.6031 | 28500 | 0.2395 | - |
613
+ | 0.6052 | 28600 | 0.2269 | - |
614
+ | 0.6074 | 28700 | 0.2639 | - |
615
+ | 0.6095 | 28800 | 0.2674 | - |
616
+ | 0.6116 | 28900 | 0.2521 | - |
617
+ | 0.6137 | 29000 | 0.2553 | - |
618
+ | 0.6158 | 29100 | 0.2526 | - |
619
+ | 0.6179 | 29200 | 0.231 | - |
620
+ | 0.6201 | 29300 | 0.2622 | - |
621
+ | 0.6222 | 29400 | 0.237 | - |
622
+ | 0.6243 | 29500 | 0.2475 | - |
623
+ | 0.6264 | 29600 | 0.2435 | - |
624
+ | 0.6285 | 29700 | 0.2109 | - |
625
+ | 0.6306 | 29800 | 0.2376 | - |
626
+ | 0.6328 | 29900 | 0.2202 | - |
627
+ | 0.6349 | 30000 | 0.2147 | 0.2370 |
628
+ | 0.6370 | 30100 | 0.2306 | - |
629
+ | 0.6391 | 30200 | 0.2249 | - |
630
+ | 0.6412 | 30300 | 0.3027 | - |
631
+ | 0.6433 | 30400 | 0.2115 | - |
632
+ | 0.6454 | 30500 | 0.2597 | - |
633
+ | 0.6476 | 30600 | 0.2483 | - |
634
+ | 0.6497 | 30700 | 0.2719 | - |
635
+ | 0.6518 | 30800 | 0.2162 | - |
636
+ | 0.6539 | 30900 | 0.2947 | - |
637
+ | 0.6560 | 31000 | 0.2144 | - |
638
+ | 0.6581 | 31100 | 0.2391 | - |
639
+ | 0.6603 | 31200 | 0.2572 | - |
640
+ | 0.6624 | 31300 | 0.1977 | - |
641
+ | 0.6645 | 31400 | 0.2678 | - |
642
+ | 0.6666 | 31500 | 0.2353 | - |
643
+ | 0.6687 | 31600 | 0.1911 | - |
644
+ | 0.6708 | 31700 | 0.2844 | - |
645
+ | 0.6730 | 31800 | 0.2689 | - |
646
+ | 0.6751 | 31900 | 0.2491 | - |
647
+ | 0.6772 | 32000 | 0.2259 | - |
648
+ | 0.6793 | 32100 | 0.2248 | - |
649
+ | 0.6814 | 32200 | 0.2462 | - |
650
+ | 0.6835 | 32300 | 0.2135 | - |
651
+ | 0.6857 | 32400 | 0.2085 | - |
652
+ | 0.6878 | 32500 | 0.227 | - |
653
+ | 0.6899 | 32600 | 0.2488 | - |
654
+ | 0.6920 | 32700 | 0.2614 | - |
655
+ | 0.6941 | 32800 | 0.2274 | - |
656
+ | 0.6962 | 32900 | 0.2389 | - |
657
+ | 0.6984 | 33000 | 0.2573 | - |
658
+ | 0.7005 | 33100 | 0.245 | - |
659
+ | 0.7026 | 33200 | 0.21 | - |
660
+ | 0.7047 | 33300 | 0.2196 | - |
661
+ | 0.7068 | 33400 | 0.2218 | - |
662
+ | 0.7089 | 33500 | 0.2092 | - |
663
+ | 0.7111 | 33600 | 0.2526 | - |
664
+ | 0.7132 | 33700 | 0.2275 | - |
665
+ | 0.7153 | 33800 | 0.2622 | - |
666
+ | 0.7174 | 33900 | 0.2469 | - |
667
+ | 0.7195 | 34000 | 0.2157 | - |
668
+ | 0.7216 | 34100 | 0.2326 | - |
669
+ | 0.7237 | 34200 | 0.268 | - |
670
+ | 0.7259 | 34300 | 0.2628 | - |
671
+ | 0.7280 | 34400 | 0.2503 | - |
672
+ | 0.7301 | 34500 | 0.2101 | - |
673
+ | 0.7322 | 34600 | 0.237 | - |
674
+ | 0.7343 | 34700 | 0.233 | - |
675
+ | 0.7364 | 34800 | 0.2077 | - |
676
+ | 0.7386 | 34900 | 0.259 | - |
677
+ | 0.7407 | 35000 | 0.2312 | 0.2284 |
678
+ | 0.7428 | 35100 | 0.287 | - |
679
+ | 0.7449 | 35200 | 0.2278 | - |
680
+ | 0.7470 | 35300 | 0.2618 | - |
681
+ | 0.7491 | 35400 | 0.2298 | - |
682
+ | 0.7513 | 35500 | 0.195 | - |
683
+ | 0.7534 | 35600 | 0.2248 | - |
684
+ | 0.7555 | 35700 | 0.2234 | - |
685
+ | 0.7576 | 35800 | 0.2218 | - |
686
+ | 0.7597 | 35900 | 0.2002 | - |
687
+ | 0.7618 | 36000 | 0.2158 | - |
688
+ | 0.7640 | 36100 | 0.1919 | - |
689
+ | 0.7661 | 36200 | 0.2972 | - |
690
+ | 0.7682 | 36300 | 0.2665 | - |
691
+ | 0.7703 | 36400 | 0.2114 | - |
692
+ | 0.7724 | 36500 | 0.1879 | - |
693
+ | 0.7745 | 36600 | 0.2137 | - |
694
+ | 0.7767 | 36700 | 0.2847 | - |
695
+ | 0.7788 | 36800 | 0.2372 | - |
696
+ | 0.7809 | 36900 | 0.2058 | - |
697
+ | 0.7830 | 37000 | 0.2205 | - |
698
+ | 0.7851 | 37100 | 0.2012 | - |
699
+ | 0.7872 | 37200 | 0.2057 | - |
700
+ | 0.7894 | 37300 | 0.1932 | - |
701
+ | 0.7915 | 37400 | 0.2261 | - |
702
+ | 0.7936 | 37500 | 0.2633 | - |
703
+ | 0.7957 | 37600 | 0.1558 | - |
704
+ | 0.7978 | 37700 | 0.2064 | - |
705
+ | 0.7999 | 37800 | 0.2166 | - |
706
+ | 0.8020 | 37900 | 0.2249 | - |
707
+ | 0.8042 | 38000 | 0.2626 | - |
708
+ | 0.8063 | 38100 | 0.1945 | - |
709
+ | 0.8084 | 38200 | 0.2611 | - |
710
+ | 0.8105 | 38300 | 0.199 | - |
711
+ | 0.8126 | 38400 | 0.2004 | - |
712
+ | 0.8147 | 38500 | 0.2506 | - |
713
+ | 0.8169 | 38600 | 0.1722 | - |
714
+ | 0.8190 | 38700 | 0.1959 | - |
715
+ | 0.8211 | 38800 | 0.2505 | - |
716
+ | 0.8232 | 38900 | 0.2343 | - |
717
+ | 0.8253 | 39000 | 0.2353 | - |
718
+ | 0.8274 | 39100 | 0.22 | - |
719
+ | 0.8296 | 39200 | 0.2089 | - |
720
+ | 0.8317 | 39300 | 0.2416 | - |
721
+ | 0.8338 | 39400 | 0.1916 | - |
722
+ | 0.8359 | 39500 | 0.2387 | - |
723
+ | 0.8380 | 39600 | 0.2475 | - |
724
+ | 0.8401 | 39700 | 0.2189 | - |
725
+ | 0.8423 | 39800 | 0.2141 | - |
726
+ | 0.8444 | 39900 | 0.2008 | - |
727
+ | 0.8465 | 40000 | 0.2489 | 0.2253 |
728
+ | 0.8486 | 40100 | 0.2258 | - |
729
+ | 0.8507 | 40200 | 0.2341 | - |
730
+ | 0.8528 | 40300 | 0.2377 | - |
731
+ | 0.8550 | 40400 | 0.194 | - |
732
+ | 0.8571 | 40500 | 0.2144 | - |
733
+ | 0.8592 | 40600 | 0.2605 | - |
734
+ | 0.8613 | 40700 | 0.2517 | - |
735
+ | 0.8634 | 40800 | 0.2044 | - |
736
+ | 0.8655 | 40900 | 0.2259 | - |
737
+ | 0.8677 | 41000 | 0.2141 | - |
738
+ | 0.8698 | 41100 | 0.1895 | - |
739
+ | 0.8719 | 41200 | 0.2361 | - |
740
+ | 0.8740 | 41300 | 0.1978 | - |
741
+ | 0.8761 | 41400 | 0.2089 | - |
742
+ | 0.8782 | 41500 | 0.2258 | - |
743
+ | 0.8803 | 41600 | 0.2368 | - |
744
+ | 0.8825 | 41700 | 0.2473 | - |
745
+ | 0.8846 | 41800 | 0.2185 | - |
746
+ | 0.8867 | 41900 | 0.212 | - |
747
+ | 0.8888 | 42000 | 0.2469 | - |
748
+ | 0.8909 | 42100 | 0.1817 | - |
749
+ | 0.8930 | 42200 | 0.1884 | - |
750
+ | 0.8952 | 42300 | 0.207 | - |
751
+ | 0.8973 | 42400 | 0.2422 | - |
752
+ | 0.8994 | 42500 | 0.2606 | - |
753
+ | 0.9015 | 42600 | 0.2266 | - |
754
+ | 0.9036 | 42700 | 0.2103 | - |
755
+ | 0.9057 | 42800 | 0.2712 | - |
756
+ | 0.9079 | 42900 | 0.1944 | - |
757
+ | 0.9100 | 43000 | 0.2003 | - |
758
+ | 0.9121 | 43100 | 0.1991 | - |
759
+ | 0.9142 | 43200 | 0.2129 | - |
760
+ | 0.9163 | 43300 | 0.2465 | - |
761
+ | 0.9184 | 43400 | 0.1764 | - |
762
+ | 0.9206 | 43500 | 0.2365 | - |
763
+ | 0.9227 | 43600 | 0.2054 | - |
764
+ | 0.9248 | 43700 | 0.2551 | - |
765
+ | 0.9269 | 43800 | 0.2322 | - |
766
+ | 0.9290 | 43900 | 0.2213 | - |
767
+ | 0.9311 | 44000 | 0.1962 | - |
768
+ | 0.9333 | 44100 | 0.1988 | - |
769
+ | 0.9354 | 44200 | 0.1982 | - |
770
+ | 0.9375 | 44300 | 0.2193 | - |
771
+ | 0.9396 | 44400 | 0.2378 | - |
772
+ | 0.9417 | 44500 | 0.2244 | - |
773
+ | 0.9438 | 44600 | 0.2296 | - |
774
+ | 0.9460 | 44700 | 0.2446 | - |
775
+ | 0.9481 | 44800 | 0.2206 | - |
776
+ | 0.9502 | 44900 | 0.1815 | - |
777
+ | **0.9523** | **45000** | **0.2385** | **0.22** |
778
+ | 0.9544 | 45100 | 0.2106 | - |
779
+ | 0.9565 | 45200 | 0.1929 | - |
780
+ | 0.9586 | 45300 | 0.181 | - |
781
+ | 0.9608 | 45400 | 0.1908 | - |
782
+ | 0.9629 | 45500 | 0.1926 | - |
783
+ | 0.9650 | 45600 | 0.1922 | - |
784
+ | 0.9671 | 45700 | 0.2003 | - |
785
+ | 0.9692 | 45800 | 0.2377 | - |
786
+ | 0.9713 | 45900 | 0.2069 | - |
787
+ | 0.9735 | 46000 | 0.2024 | - |
788
+ | 0.9756 | 46100 | 0.1795 | - |
789
+ | 0.9777 | 46200 | 0.2372 | - |
790
+ | 0.9798 | 46300 | 0.2135 | - |
791
+ | 0.9819 | 46400 | 0.2396 | - |
792
+ | 0.9840 | 46500 | 0.2295 | - |
793
+ | 0.9862 | 46600 | 0.2235 | - |
794
+ | 0.9883 | 46700 | 0.2427 | - |
795
+ | 0.9904 | 46800 | 0.2145 | - |
796
+ | 0.9925 | 46900 | 0.2231 | - |
797
+ | 0.9946 | 47000 | 0.2401 | - |
798
+ | 0.9967 | 47100 | 0.1764 | - |
799
+ | 0.9989 | 47200 | 0.1943 | - |
800
+
801
+ * The bold row denotes the saved checkpoint.
802
+ </details>
803
+
804
+ ### Framework Versions
805
+ - Python: 3.12.4
806
+ - Sentence Transformers: 3.1.0.dev0
807
+ - Transformers: 4.42.4
808
+ - PyTorch: 2.3.1+cpu
809
+ - Accelerate: 0.32.1
810
+ - Datasets: 2.20.0
811
+ - Tokenizers: 0.19.1
812
+
813
+ ## Citation
814
+
815
+ ### BibTeX
816
+
817
+ #### Sentence Transformers
818
+ ```bibtex
819
+ @inproceedings{reimers-2019-sentence-bert,
820
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
821
+ author = "Reimers, Nils and Gurevych, Iryna",
822
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
823
+ month = "11",
824
+ year = "2019",
825
+ publisher = "Association for Computational Linguistics",
826
+ url = "https://arxiv.org/abs/1908.10084",
827
+ }
828
+ ```
829
+
830
+ #### MultipleNegativesRankingLoss
831
+ ```bibtex
832
+ @misc{henderson2017efficient,
833
+ title={Efficient Natural Language Response Suggestion for Smart Reply},
834
+ author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
835
+ year={2017},
836
+ eprint={1705.00652},
837
+ archivePrefix={arXiv},
838
+ primaryClass={cs.CL}
839
+ }
840
+ ```
841
+
842
+ <!--
843
+ ## Glossary
844
+
845
+ *Clearly define terms in order to be accessible across audiences.*
846
+ -->
847
+
848
+ <!--
849
+ ## Model Card Authors
850
+
851
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
852
+ -->
853
+
854
+ <!--
855
+ ## Model Card Contact
856
+
857
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
858
+ -->
final/config.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
3
+ "architectures": [
4
+ "MPNetModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 768,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 3072,
14
+ "layer_norm_eps": 1e-05,
15
+ "max_position_embeddings": 514,
16
+ "model_type": "mpnet",
17
+ "num_attention_heads": 12,
18
+ "num_hidden_layers": 12,
19
+ "pad_token_id": 1,
20
+ "relative_attention_num_buckets": 32,
21
+ "torch_dtype": "float32",
22
+ "transformers_version": "4.42.4",
23
+ "vocab_size": 30527
24
+ }
final/config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.1.0.dev0",
4
+ "transformers": "4.42.4",
5
+ "pytorch": "2.3.1+cpu"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": null
10
+ }
final/model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6e981daa41a8b51b959a05b4c15a733ddb286d5b68010884eb5d3c7b8b9987a4
3
+ size 437967672
final/modules.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ {
15
+ "idx": 2,
16
+ "name": "2",
17
+ "path": "2_Normalize",
18
+ "type": "sentence_transformers.models.Normalize"
19
+ }
20
+ ]
final/sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 384,
3
+ "do_lower_case": false
4
+ }
final/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
+ }
final/tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
final/tokenizer_config.json ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": true,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "104": {
36
+ "content": "[UNK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "30526": {
44
+ "content": "<mask>",
45
+ "lstrip": true,
46
+ "normalized": false,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": true
50
+ }
51
+ },
52
+ "bos_token": "<s>",
53
+ "clean_up_tokenization_spaces": true,
54
+ "cls_token": "<s>",
55
+ "do_lower_case": true,
56
+ "eos_token": "</s>",
57
+ "mask_token": "<mask>",
58
+ "max_length": 128,
59
+ "model_max_length": 384,
60
+ "pad_to_multiple_of": null,
61
+ "pad_token": "<pad>",
62
+ "pad_token_type_id": 0,
63
+ "padding_side": "right",
64
+ "sep_token": "</s>",
65
+ "stride": 0,
66
+ "strip_accents": null,
67
+ "tokenize_chinese_chars": true,
68
+ "tokenizer_class": "MPNetTokenizer",
69
+ "truncation_side": "right",
70
+ "truncation_strategy": "longest_first",
71
+ "unk_token": "[UNK]"
72
+ }
final/vocab.txt ADDED
The diff for this file is too large to render. See raw diff