Hugging Face's logo

yahyaabd
/
allstats-semantic-search-model-v1-3-origin

Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:212940
loss:CosineSimilarityLoss
Eval Results
text-embeddings-inference
Inference Endpoints
Model card Files Community
yahyaabd commited on
Commit
bc6b994
·
verified ·
1 Parent(s): f2f6076

Add new SentenceTransformer model

Browse files
Files changed (11) hide show
  1. .gitattributes +1 -0
  2. 1_Pooling/config.json +10 -0
  3. README.md +587 -0
  4. config.json +29 -0
  5. config_sentence_transformers.json +10 -0
  6. model.safetensors +3 -0
  7. modules.json +14 -0
  8. sentence_bert_config.json +4 -0
  9. special_tokens_map.json +51 -0
  10. tokenizer.json +3 -0
  11. tokenizer_config.json +62 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
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
+ }
README.md ADDED
@@ -0,0 +1,587 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - sentence-transformers
4
+ - sentence-similarity
5
+ - feature-extraction
6
+ - generated_from_trainer
7
+ - dataset_size:212940
8
+ - loss:CosineSimilarityLoss
9
+ base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
10
+ widget:
11
+ - source_sentence: Ringkasan data strategis BPS 2012
12
+ sentences:
13
+ - Rata-rata Upah/Gaji Bersih Sebulan Buruh/Karyawan/Pegawai Menurut Provinsi dan
14
+ Jenis Pekerjaan Utama, 2021
15
+ - Laporan Perekonomian Indonesia 2007
16
+ - Statistik Potensi Desa Provinsi Banten 2008
17
+ - source_sentence: tahun berapa ekspor naik 2,37% dan impor naik 30,30%?
18
+ sentences:
19
+ - Bulan November 2006 Ekspor Naik 2,37 % dan Impor Naik 30,30 %
20
+ - Indeks Harga Konsumen per Kelompok di 82 Kota <sup>1</sup> (2012=100)
21
+ - 'Februari 2022: Tingkat Pengangguran Terbuka (TPT) sebesar 5,83 persen dan Rata-rata
22
+ upah buruh sebesar 2,89 juta rupiah per bulan'
23
+ - source_sentence: akses air bersih di indonesia (2005-2009)
24
+ sentences:
25
+ - Desember 2016, Rupiah Terapresiasi 0,74 Persen Terhadap Dolar Amerika
26
+ - Statistik Air Bersih 2005-2009
27
+ - Rata-rata Upah/Gaji Bersih Sebulan Buruh/Karyawan/Pegawai Menurut Pendidikan Tertinggi
28
+ yang Ditamatkan dan Lapangan Pekerjaan Utama di 17 Sektor (rupiah), 2018
29
+ - source_sentence: Tinjauan Regional Berdasarkan PDRB Kabupaten/Kota 2014-2018, Buku
30
+ 2 Pulau Jawa dan Bali
31
+ sentences:
32
+ - Profil Migran Hasil Susenas 2011-2012
33
+ - Statistik Gas Kota 2004-2008
34
+ - Jumlah kunjungan wisman ke Indonesia melalui pintu masuk utama pada Juni 2022
35
+ mencapai 345,44 ribu kunjungan dan Jumlah penumpang angkutan udara internasional
36
+ pada Juni 2022 naik 23,28 persen
37
+ - source_sentence: perubahan nilai tukar petani bulan mei 2017
38
+ sentences:
39
+ - Perkembangan Nilai Tukar Petani Mei 2017
40
+ - NTP Naik 0,15%, Harga Gabah Kualitas GKG Naik 0,98%
41
+ - Statistik Restoran/Rumah Makan Tahun 2014
42
+ datasets:
43
+ - yahyaabd/allstats-semantic-search-synthetic-dataset-v1
44
+ pipeline_tag: sentence-similarity
45
+ library_name: sentence-transformers
46
+ metrics:
47
+ - pearson_cosine
48
+ - spearman_cosine
49
+ model-index:
50
+ - name: SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2
51
+ results:
52
+ - task:
53
+ type: semantic-similarity
54
+ name: Semantic Similarity
55
+ dataset:
56
+ name: allstats semantic search v1 3 dev
57
+ type: allstats-semantic-search-v1-3-dev
58
+ metrics:
59
+ - type: pearson_cosine
60
+ value: 0.9955935469233214
61
+ name: Pearson Cosine
62
+ - type: spearman_cosine
63
+ value: 0.9588270212992008
64
+ name: Spearman Cosine
65
+ - task:
66
+ type: semantic-similarity
67
+ name: Semantic Similarity
68
+ dataset:
69
+ name: allstat semantic search v1 3 test
70
+ type: allstat-semantic-search-v1-3-test
71
+ metrics:
72
+ - type: pearson_cosine
73
+ value: 0.9955194411367296
74
+ name: Pearson Cosine
75
+ - type: spearman_cosine
76
+ value: 0.958337873285875
77
+ name: Spearman Cosine
78
+ ---
79
+
80
+ # SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2
81
+
82
+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) on the [allstats-semantic-search-synthetic-dataset-v1](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1) dataset. 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.
83
+
84
+ ## Model Details
85
+
86
+ ### Model Description
87
+ - **Model Type:** Sentence Transformer
88
+ - **Base model:** [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) <!-- at revision 75c57757a97f90ad739aca51fa8bfea0e485a7f2 -->
89
+ - **Maximum Sequence Length:** 128 tokens
90
+ - **Output Dimensionality:** 768 dimensions
91
+ - **Similarity Function:** Cosine Similarity
92
+ - **Training Dataset:**
93
+ - [allstats-semantic-search-synthetic-dataset-v1](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1)
94
+ <!-- - **Language:** Unknown -->
95
+ <!-- - **License:** Unknown -->
96
+
97
+ ### Model Sources
98
+
99
+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
100
+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
101
+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
102
+
103
+ ### Full Model Architecture
104
+
105
+ ```
106
+ SentenceTransformer(
107
+ (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
108
+ (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})
109
+ )
110
+ ```
111
+
112
+ ## Usage
113
+
114
+ ### Direct Usage (Sentence Transformers)
115
+
116
+ First install the Sentence Transformers library:
117
+
118
+ ```bash
119
+ pip install -U sentence-transformers
120
+ ```
121
+
122
+ Then you can load this model and run inference.
123
+ ```python
124
+ from sentence_transformers import SentenceTransformer
125
+
126
+ # Download from the 🤗 Hub
127
+ model = SentenceTransformer("yahyaabd/allstats-semantic-search-model-v1-3")
128
+ # Run inference
129
+ sentences = [
130
+ 'perubahan nilai tukar petani bulan mei 2017',
131
+ 'Perkembangan Nilai Tukar Petani Mei 2017',
132
+ 'Statistik Restoran/Rumah Makan Tahun 2014',
133
+ ]
134
+ embeddings = model.encode(sentences)
135
+ print(embeddings.shape)
136
+ # [3, 768]
137
+
138
+ # Get the similarity scores for the embeddings
139
+ similarities = model.similarity(embeddings, embeddings)
140
+ print(similarities.shape)
141
+ # [3, 3]
142
+ ```
143
+
144
+ <!--
145
+ ### Direct Usage (Transformers)
146
+
147
+ <details><summary>Click to see the direct usage in Transformers</summary>
148
+
149
+ </details>
150
+ -->
151
+
152
+ <!--
153
+ ### Downstream Usage (Sentence Transformers)
154
+
155
+ You can finetune this model on your own dataset.
156
+
157
+ <details><summary>Click to expand</summary>
158
+
159
+ </details>
160
+ -->
161
+
162
+ <!--
163
+ ### Out-of-Scope Use
164
+
165
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
166
+ -->
167
+
168
+ ## Evaluation
169
+
170
+ ### Metrics
171
+
172
+ #### Semantic Similarity
173
+
174
+ * Datasets: `allstats-semantic-search-v1-3-dev` and `allstat-semantic-search-v1-3-test`
175
+ * Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
176
+
177
+ | Metric | allstats-semantic-search-v1-3-dev | allstat-semantic-search-v1-3-test |
178
+ |:--------------------|:----------------------------------|:----------------------------------|
179
+ | pearson_cosine | 0.9956 | 0.9955 |
180
+ | **spearman_cosine** | **0.9588** | **0.9583** |
181
+
182
+ <!--
183
+ ## Bias, Risks and Limitations
184
+
185
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
186
+ -->
187
+
188
+ <!--
189
+ ### Recommendations
190
+
191
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
192
+ -->
193
+
194
+ ## Training Details
195
+
196
+ ### Training Dataset
197
+
198
+ #### allstats-semantic-search-synthetic-dataset-v1
199
+
200
+ * Dataset: [allstats-semantic-search-synthetic-dataset-v1](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1) at [b13c0a7](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1/tree/b13c0a7412396a836cfbb887e140f183f3a6d65e)
201
+ * Size: 212,940 training samples
202
+ * Columns: <code>query</code>, <code>doc</code>, and <code>label</code>
203
+ * Approximate statistics based on the first 1000 samples:
204
+ | | query | doc | label |
205
+ |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------|
206
+ | type | string | string | float |
207
+ | details | <ul><li>min: 5 tokens</li><li>mean: 11.46 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 14.47 tokens</li><li>max: 54 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.5</li><li>max: 1.05</li></ul> |
208
+ * Samples:
209
+ | query | doc | label |
210
+ |:---------------------------------------------------------------|:-----------------------------------------------------------------------|:------------------|
211
+ | <code>aDta industri besar dan sedang Indonesia 2008</code> | <code>Statistik Industri Besar dan Sedang Indonesia 2008</code> | <code>0.9</code> |
212
+ | <code>profil bisnis konstruksi individu jawa barat 2022</code> | <code>Statistik Industri Manufaktur Indonesia 2015 - Bahan Baku</code> | <code>0.15</code> |
213
+ | <code>data statistik ekonomi indonesia</code> | <code>Nilai Tukar Valuta Asing di Indonesia 2014</code> | <code>0.08</code> |
214
+ * Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
215
+ ```json
216
+ {
217
+ "loss_fct": "torch.nn.modules.loss.MSELoss"
218
+ }
219
+ ```
220
+
221
+ ### Evaluation Dataset
222
+
223
+ #### allstats-semantic-search-synthetic-dataset-v1
224
+
225
+ * Dataset: [allstats-semantic-search-synthetic-dataset-v1](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1) at [b13c0a7](https://huggingface.co/datasets/yahyaabd/allstats-semantic-search-synthetic-dataset-v1/tree/b13c0a7412396a836cfbb887e140f183f3a6d65e)
226
+ * Size: 26,618 evaluation samples
227
+ * Columns: <code>query</code>, <code>doc</code>, and <code>label</code>
228
+ * Approximate statistics based on the first 1000 samples:
229
+ | | query | doc | label |
230
+ |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:---------------------------------------------------------------|
231
+ | type | string | string | float |
232
+ | details | <ul><li>min: 5 tokens</li><li>mean: 11.38 tokens</li><li>max: 34 tokens</li></ul> | <ul><li>min: 4 tokens</li><li>mean: 14.63 tokens</li><li>max: 55 tokens</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.51</li><li>max: 1.0</li></ul> |
233
+ * Samples:
234
+ | query | doc | label |
235
+ |:-------------------------------------------------------------------|:---------------------------------------------------------------------------|:------------------|
236
+ | <code>tahun berapa ekspor naik 2,37% dan impor naik 30,30%?</code> | <code>Bulan November 2006 Ekspor Naik 2,37 % dan Impor Naik 30,30 %</code> | <code>1.0</code> |
237
+ | <code>Berapa produksi padi pada tahun 2023?</code> | <code>Produksi padi tahun lainnya</code> | <code>0.0</code> |
238
+ | <code>data statistik solus per aqua 2015</code> | <code>Statistik Solus Per Aqua (SPA) 2015</code> | <code>0.97</code> |
239
+ * Loss: [<code>CosineSimilarityLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosinesimilarityloss) with these parameters:
240
+ ```json
241
+ {
242
+ "loss_fct": "torch.nn.modules.loss.MSELoss"
243
+ }
244
+ ```
245
+
246
+ ### Training Hyperparameters
247
+ #### Non-Default Hyperparameters
248
+
249
+ - `eval_strategy`: steps
250
+ - `per_device_train_batch_size`: 32
251
+ - `per_device_eval_batch_size`: 32
252
+ - `num_train_epochs`: 12
253
+ - `warmup_ratio`: 0.1
254
+ - `fp16`: True
255
+
256
+ #### All Hyperparameters
257
+ <details><summary>Click to expand</summary>
258
+
259
+ - `overwrite_output_dir`: False
260
+ - `do_predict`: False
261
+ - `eval_strategy`: steps
262
+ - `prediction_loss_only`: True
263
+ - `per_device_train_batch_size`: 32
264
+ - `per_device_eval_batch_size`: 32
265
+ - `per_gpu_train_batch_size`: None
266
+ - `per_gpu_eval_batch_size`: None
267
+ - `gradient_accumulation_steps`: 1
268
+ - `eval_accumulation_steps`: None
269
+ - `torch_empty_cache_steps`: None
270
+ - `learning_rate`: 5e-05
271
+ - `weight_decay`: 0.0
272
+ - `adam_beta1`: 0.9
273
+ - `adam_beta2`: 0.999
274
+ - `adam_epsilon`: 1e-08
275
+ - `max_grad_norm`: 1.0
276
+ - `num_train_epochs`: 12
277
+ - `max_steps`: -1
278
+ - `lr_scheduler_type`: linear
279
+ - `lr_scheduler_kwargs`: {}
280
+ - `warmup_ratio`: 0.1
281
+ - `warmup_steps`: 0
282
+ - `log_level`: passive
283
+ - `log_level_replica`: warning
284
+ - `log_on_each_node`: True
285
+ - `logging_nan_inf_filter`: True
286
+ - `save_safetensors`: True
287
+ - `save_on_each_node`: False
288
+ - `save_only_model`: False
289
+ - `restore_callback_states_from_checkpoint`: False
290
+ - `no_cuda`: False
291
+ - `use_cpu`: False
292
+ - `use_mps_device`: False
293
+ - `seed`: 42
294
+ - `data_seed`: None
295
+ - `jit_mode_eval`: False
296
+ - `use_ipex`: False
297
+ - `bf16`: False
298
+ - `fp16`: True
299
+ - `fp16_opt_level`: O1
300
+ - `half_precision_backend`: auto
301
+ - `bf16_full_eval`: False
302
+ - `fp16_full_eval`: False
303
+ - `tf32`: None
304
+ - `local_rank`: 0
305
+ - `ddp_backend`: None
306
+ - `tpu_num_cores`: None
307
+ - `tpu_metrics_debug`: False
308
+ - `debug`: []
309
+ - `dataloader_drop_last`: False
310
+ - `dataloader_num_workers`: 0
311
+ - `dataloader_prefetch_factor`: None
312
+ - `past_index`: -1
313
+ - `disable_tqdm`: False
314
+ - `remove_unused_columns`: True
315
+ - `label_names`: None
316
+ - `load_best_model_at_end`: False
317
+ - `ignore_data_skip`: False
318
+ - `fsdp`: []
319
+ - `fsdp_min_num_params`: 0
320
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
321
+ - `fsdp_transformer_layer_cls_to_wrap`: None
322
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
323
+ - `deepspeed`: None
324
+ - `label_smoothing_factor`: 0.0
325
+ - `optim`: adamw_torch
326
+ - `optim_args`: None
327
+ - `adafactor`: False
328
+ - `group_by_length`: False
329
+ - `length_column_name`: length
330
+ - `ddp_find_unused_parameters`: None
331
+ - `ddp_bucket_cap_mb`: None
332
+ - `ddp_broadcast_buffers`: False
333
+ - `dataloader_pin_memory`: True
334
+ - `dataloader_persistent_workers`: False
335
+ - `skip_memory_metrics`: True
336
+ - `use_legacy_prediction_loop`: False
337
+ - `push_to_hub`: False
338
+ - `resume_from_checkpoint`: None
339
+ - `hub_model_id`: None
340
+ - `hub_strategy`: every_save
341
+ - `hub_private_repo`: None
342
+ - `hub_always_push`: False
343
+ - `gradient_checkpointing`: False
344
+ - `gradient_checkpointing_kwargs`: None
345
+ - `include_inputs_for_metrics`: False
346
+ - `include_for_metrics`: []
347
+ - `eval_do_concat_batches`: True
348
+ - `fp16_backend`: auto
349
+ - `push_to_hub_model_id`: None
350
+ - `push_to_hub_organization`: None
351
+ - `mp_parameters`:
352
+ - `auto_find_batch_size`: False
353
+ - `full_determinism`: False
354
+ - `torchdynamo`: None
355
+ - `ray_scope`: last
356
+ - `ddp_timeout`: 1800
357
+ - `torch_compile`: False
358
+ - `torch_compile_backend`: None
359
+ - `torch_compile_mode`: None
360
+ - `dispatch_batches`: None
361
+ - `split_batches`: None
362
+ - `include_tokens_per_second`: False
363
+ - `include_num_input_tokens_seen`: False
364
+ - `neftune_noise_alpha`: None
365
+ - `optim_target_modules`: None
366
+ - `batch_eval_metrics`: False
367
+ - `eval_on_start`: False
368
+ - `use_liger_kernel`: False
369
+ - `eval_use_gather_object`: False
370
+ - `average_tokens_across_devices`: False
371
+ - `prompts`: None
372
+ - `batch_sampler`: batch_sampler
373
+ - `multi_dataset_batch_sampler`: proportional
374
+
375
+ </details>
376
+
377
+ ### Training Logs
378
+ <details><summary>Click to expand</summary>
379
+
380
+ | Epoch | Step | Training Loss | Validation Loss | allstats-semantic-search-v1-3-dev_spearman_cosine | allstat-semantic-search-v1-3-test_spearman_cosine |
381
+ |:-------:|:-----:|:-------------:|:---------------:|:-------------------------------------------------:|:-------------------------------------------------:|
382
+ | 0.0751 | 500 | 0.0653 | 0.0400 | 0.7035 | - |
383
+ | 0.1503 | 1000 | 0.0361 | 0.0296 | 0.7310 | - |
384
+ | 0.2254 | 1500 | 0.0278 | 0.0226 | 0.7669 | - |
385
+ | 0.3005 | 2000 | 0.0226 | 0.0195 | 0.7748 | - |
386
+ | 0.3757 | 2500 | 0.0208 | 0.0183 | 0.7769 | - |
387
+ | 0.4508 | 3000 | 0.0184 | 0.0172 | 0.7994 | - |
388
+ | 0.5259 | 3500 | 0.0179 | 0.0159 | 0.7931 | - |
389
+ | 0.6011 | 4000 | 0.0159 | 0.0155 | 0.7966 | - |
390
+ | 0.6762 | 4500 | 0.0161 | 0.0150 | 0.8047 | - |
391
+ | 0.7513 | 5000 | 0.0163 | 0.0153 | 0.7910 | - |
392
+ | 0.8264 | 5500 | 0.0158 | 0.0155 | 0.7956 | - |
393
+ | 0.9016 | 6000 | 0.0149 | 0.0141 | 0.8148 | - |
394
+ | 0.9767 | 6500 | 0.0149 | 0.0145 | 0.8287 | - |
395
+ | 1.0518 | 7000 | 0.0148 | 0.0150 | 0.7933 | - |
396
+ | 1.1270 | 7500 | 0.0131 | 0.0136 | 0.8083 | - |
397
+ | 1.2021 | 8000 | 0.0124 | 0.0131 | 0.8173 | - |
398
+ | 1.2772 | 8500 | 0.0133 | 0.0130 | 0.8117 | - |
399
+ | 1.3524 | 9000 | 0.012 | 0.0126 | 0.8259 | - |
400
+ | 1.4275 | 9500 | 0.0119 | 0.0120 | 0.8178 | - |
401
+ | 1.5026 | 10000 | 0.0116 | 0.0118 | 0.8332 | - |
402
+ | 1.5778 | 10500 | 0.0132 | 0.0123 | 0.8108 | - |
403
+ | 1.6529 | 11000 | 0.0114 | 0.0111 | 0.8365 | - |
404
+ | 1.7280 | 11500 | 0.0105 | 0.0109 | 0.8235 | - |
405
+ | 1.8032 | 12000 | 0.0107 | 0.0105 | 0.8445 | - |
406
+ | 1.8783 | 12500 | 0.0106 | 0.0101 | 0.8330 | - |
407
+ | 1.9534 | 13000 | 0.0095 | 0.0096 | 0.8437 | - |
408
+ | 2.0285 | 13500 | 0.0093 | 0.0094 | 0.8417 | - |
409
+ | 2.1037 | 14000 | 0.0079 | 0.0093 | 0.8485 | - |
410
+ | 2.1788 | 14500 | 0.008 | 0.0089 | 0.8422 | - |
411
+ | 2.2539 | 15000 | 0.0081 | 0.0086 | 0.8485 | - |
412
+ | 2.3291 | 15500 | 0.008 | 0.0084 | 0.8530 | - |
413
+ | 2.4042 | 16000 | 0.007 | 0.0084 | 0.8597 | - |
414
+ | 2.4793 | 16500 | 0.0081 | 0.0087 | 0.8499 | - |
415
+ | 2.5545 | 17000 | 0.0078 | 0.0078 | 0.8577 | - |
416
+ | 2.6296 | 17500 | 0.007 | 0.0080 | 0.8559 | - |
417
+ | 2.7047 | 18000 | 0.0072 | 0.0078 | 0.8569 | - |
418
+ | 2.7799 | 18500 | 0.0069 | 0.0079 | 0.8579 | - |
419
+ | 2.8550 | 19000 | 0.0064 | 0.0072 | 0.8693 | - |
420
+ | 2.9301 | 19500 | 0.0064 | 0.0070 | 0.8747 | - |
421
+ | 3.0053 | 20000 | 0.0061 | 0.0068 | 0.8757 | - |
422
+ | 3.0804 | 20500 | 0.0052 | 0.0069 | 0.8727 | - |
423
+ | 3.1555 | 21000 | 0.005 | 0.0067 | 0.8734 | - |
424
+ | 3.2307 | 21500 | 0.0054 | 0.0065 | 0.8727 | - |
425
+ | 3.3058 | 22000 | 0.0058 | 0.0070 | 0.8715 | - |
426
+ | 3.3809 | 22500 | 0.0056 | 0.0066 | 0.8724 | - |
427
+ | 3.4560 | 23000 | 0.0056 | 0.0070 | 0.8740 | - |
428
+ | 3.5312 | 23500 | 0.0054 | 0.0060 | 0.8775 | - |
429
+ | 3.6063 | 24000 | 0.0051 | 0.0062 | 0.8746 | - |
430
+ | 3.6814 | 24500 | 0.0047 | 0.0060 | 0.8765 | - |
431
+ | 3.7566 | 25000 | 0.0051 | 0.0067 | 0.8783 | - |
432
+ | 3.8317 | 25500 | 0.0048 | 0.0058 | 0.8824 | - |
433
+ | 3.9068 | 26000 | 0.0048 | 0.0059 | 0.8862 | - |
434
+ | 3.9820 | 26500 | 0.005 | 0.0056 | 0.8853 | - |
435
+ | 4.0571 | 27000 | 0.0042 | 0.0053 | 0.8868 | - |
436
+ | 4.1322 | 27500 | 0.0036 | 0.0056 | 0.8893 | - |
437
+ | 4.2074 | 28000 | 0.0041 | 0.0052 | 0.8954 | - |
438
+ | 4.2825 | 28500 | 0.0041 | 0.0050 | 0.8943 | - |
439
+ | 4.3576 | 29000 | 0.0036 | 0.0050 | 0.8890 | - |
440
+ | 4.4328 | 29500 | 0.0036 | 0.0046 | 0.8990 | - |
441
+ | 4.5079 | 30000 | 0.0038 | 0.0051 | 0.8934 | - |
442
+ | 4.5830 | 30500 | 0.0037 | 0.0049 | 0.9011 | - |
443
+ | 4.6582 | 31000 | 0.0036 | 0.0049 | 0.9000 | - |
444
+ | 4.7333 | 31500 | 0.0041 | 0.0052 | 0.8938 | - |
445
+ | 4.8084 | 32000 | 0.004 | 0.0049 | 0.8971 | - |
446
+ | 4.8835 | 32500 | 0.0038 | 0.0043 | 0.9023 | - |
447
+ | 4.9587 | 33000 | 0.0036 | 0.0044 | 0.9006 | - |
448
+ | 5.0338 | 33500 | 0.0032 | 0.0043 | 0.9042 | - |
449
+ | 5.1089 | 34000 | 0.0031 | 0.0042 | 0.9054 | - |
450
+ | 5.1841 | 34500 | 0.0028 | 0.0042 | 0.9052 | - |
451
+ | 5.2592 | 35000 | 0.0028 | 0.0043 | 0.9065 | - |
452
+ | 5.3343 | 35500 | 0.003 | 0.0041 | 0.9093 | - |
453
+ | 5.4095 | 36000 | 0.0029 | 0.0042 | 0.9084 | - |
454
+ | 5.4846 | 36500 | 0.0029 | 0.0044 | 0.9078 | - |
455
+ | 5.5597 | 37000 | 0.0027 | 0.0043 | 0.9062 | - |
456
+ | 5.6349 | 37500 | 0.003 | 0.0039 | 0.9101 | - |
457
+ | 5.7100 | 38000 | 0.0027 | 0.0041 | 0.9092 | - |
458
+ | 5.7851 | 38500 | 0.0025 | 0.0039 | 0.9140 | - |
459
+ | 5.8603 | 39000 | 0.0027 | 0.0037 | 0.9138 | - |
460
+ | 5.9354 | 39500 | 0.0027 | 0.0037 | 0.9137 | - |
461
+ | 6.0105 | 40000 | 0.0027 | 0.0036 | 0.9162 | - |
462
+ | 6.0856 | 40500 | 0.002 | 0.0035 | 0.9209 | - |
463
+ | 6.1608 | 41000 | 0.0021 | 0.0037 | 0.9180 | - |
464
+ | 6.2359 | 41500 | 0.0023 | 0.0036 | 0.9183 | - |
465
+ | 6.3110 | 42000 | 0.0024 | 0.0035 | 0.9218 | - |
466
+ | 6.3862 | 42500 | 0.002 | 0.0033 | 0.9216 | - |
467
+ | 6.4613 | 43000 | 0.0024 | 0.0035 | 0.9220 | - |
468
+ | 6.5364 | 43500 | 0.0018 | 0.0034 | 0.9232 | - |
469
+ | 6.6116 | 44000 | 0.0021 | 0.0033 | 0.9236 | - |
470
+ | 6.6867 | 44500 | 0.0021 | 0.0035 | 0.9225 | - |
471
+ | 6.7618 | 45000 | 0.0027 | 0.0031 | 0.9227 | - |
472
+ | 6.8370 | 45500 | 0.0019 | 0.0032 | 0.9242 | - |
473
+ | 6.9121 | 46000 | 0.0022 | 0.0033 | 0.9224 | - |
474
+ | 6.9872 | 46500 | 0.0022 | 0.0030 | 0.9252 | - |
475
+ | 7.0624 | 47000 | 0.0017 | 0.0029 | 0.9294 | - |
476
+ | 7.1375 | 47500 | 0.0014 | 0.0028 | 0.9304 | - |
477
+ | 7.2126 | 48000 | 0.0015 | 0.0028 | 0.9324 | - |
478
+ | 7.2878 | 48500 | 0.0014 | 0.0030 | 0.9313 | - |
479
+ | 7.3629 | 49000 | 0.0015 | 0.0029 | 0.9333 | - |
480
+ | 7.4380 | 49500 | 0.0015 | 0.0028 | 0.9342 | - |
481
+ | 7.5131 | 50000 | 0.0018 | 0.0030 | 0.9261 | - |
482
+ | 7.5883 | 50500 | 0.0016 | 0.0030 | 0.9329 | - |
483
+ | 7.6634 | 51000 | 0.0019 | 0.0026 | 0.9334 | - |
484
+ | 7.7385 | 51500 | 0.0018 | 0.0029 | 0.9336 | - |
485
+ | 7.8137 | 52000 | 0.0016 | 0.0026 | 0.9353 | - |
486
+ | 7.8888 | 52500 | 0.0016 | 0.0026 | 0.9351 | - |
487
+ | 7.9639 | 53000 | 0.0017 | 0.0024 | 0.9356 | - |
488
+ | 8.0391 | 53500 | 0.0013 | 0.0023 | 0.9396 | - |
489
+ | 8.1142 | 54000 | 0.0012 | 0.0024 | 0.9390 | - |
490
+ | 8.1893 | 54500 | 0.001 | 0.0024 | 0.9421 | - |
491
+ | 8.2645 | 55000 | 0.0012 | 0.0024 | 0.9406 | - |
492
+ | 8.3396 | 55500 | 0.0012 | 0.0023 | 0.9407 | - |
493
+ | 8.4147 | 56000 | 0.0012 | 0.0024 | 0.9398 | - |
494
+ | 8.4899 | 56500 | 0.0012 | 0.0024 | 0.9412 | - |
495
+ | 8.5650 | 57000 | 0.0014 | 0.0024 | 0.9397 | - |
496
+ | 8.6401 | 57500 | 0.0013 | 0.0023 | 0.9411 | - |
497
+ | 8.7153 | 58000 | 0.0013 | 0.0023 | 0.9418 | - |
498
+ | 8.7904 | 58500 | 0.0014 | 0.0022 | 0.9432 | - |
499
+ | 8.8655 | 59000 | 0.0011 | 0.0022 | 0.9448 | - |
500
+ | 8.9406 | 59500 | 0.0012 | 0.0022 | 0.9455 | - |
501
+ | 9.0158 | 60000 | 0.0012 | 0.0021 | 0.9453 | - |
502
+ | 9.0909 | 60500 | 0.0009 | 0.0021 | 0.9461 | - |
503
+ | 9.1660 | 61000 | 0.0009 | 0.0021 | 0.9465 | - |
504
+ | 9.2412 | 61500 | 0.0009 | 0.0021 | 0.9471 | - |
505
+ | 9.3163 | 62000 | 0.0009 | 0.0021 | 0.9477 | - |
506
+ | 9.3914 | 62500 | 0.0008 | 0.0020 | 0.9482 | - |
507
+ | 9.4666 | 63000 | 0.0012 | 0.0020 | 0.9478 | - |
508
+ | 9.5417 | 63500 | 0.0009 | 0.0020 | 0.9479 | - |
509
+ | 9.6168 | 64000 | 0.0009 | 0.0020 | 0.9485 | - |
510
+ | 9.6920 | 64500 | 0.0011 | 0.0020 | 0.9492 | - |
511
+ | 9.7671 | 65000 | 0.0008 | 0.0019 | 0.9497 | - |
512
+ | 9.8422 | 65500 | 0.001 | 0.0019 | 0.9504 | - |
513
+ | 9.9174 | 66000 | 0.0009 | 0.0019 | 0.9518 | - |
514
+ | 9.9925 | 66500 | 0.0009 | 0.0019 | 0.9510 | - |
515
+ | 10.0676 | 67000 | 0.0008 | 0.0018 | 0.9517 | - |
516
+ | 10.1427 | 67500 | 0.0007 | 0.0018 | 0.9524 | - |
517
+ | 10.2179 | 68000 | 0.0007 | 0.0018 | 0.9521 | - |
518
+ | 10.2930 | 68500 | 0.0008 | 0.0019 | 0.9526 | - |
519
+ | 10.3681 | 69000 | 0.0007 | 0.0019 | 0.9529 | - |
520
+ | 10.4433 | 69500 | 0.0008 | 0.0018 | 0.9541 | - |
521
+ | 10.5184 | 70000 | 0.0007 | 0.0017 | 0.9551 | - |
522
+ | 10.5935 | 70500 | 0.0007 | 0.0018 | 0.9550 | - |
523
+ | 10.6687 | 71000 | 0.0008 | 0.0017 | 0.9554 | - |
524
+ | 10.7438 | 71500 | 0.0007 | 0.0017 | 0.9558 | - |
525
+ | 10.8189 | 72000 | 0.0007 | 0.0018 | 0.9558 | - |
526
+ | 10.8941 | 72500 | 0.0007 | 0.0018 | 0.9562 | - |
527
+ | 10.9692 | 73000 | 0.0009 | 0.0017 | 0.9559 | - |
528
+ | 11.0443 | 73500 | 0.0005 | 0.0017 | 0.9571 | - |
529
+ | 11.1195 | 74000 | 0.0006 | 0.0017 | 0.9570 | - |
530
+ | 11.1946 | 74500 | 0.0005 | 0.0017 | 0.9573 | - |
531
+ | 11.2697 | 75000 | 0.0005 | 0.0017 | 0.9574 | - |
532
+ | 11.3449 | 75500 | 0.0006 | 0.0017 | 0.9576 | - |
533
+ | 11.4200 | 76000 | 0.0006 | 0.0017 | 0.9577 | - |
534
+ | 11.4951 | 76500 | 0.0006 | 0.0017 | 0.9577 | - |
535
+ | 11.5702 | 77000 | 0.0005 | 0.0016 | 0.9582 | - |
536
+ | 11.6454 | 77500 | 0.0006 | 0.0017 | 0.9583 | - |
537
+ | 11.7205 | 78000 | 0.0005 | 0.0016 | 0.9584 | - |
538
+ | 11.7956 | 78500 | 0.0005 | 0.0016 | 0.9587 | - |
539
+ | 11.8708 | 79000 | 0.0005 | 0.0016 | 0.9588 | - |
540
+ | 11.9459 | 79500 | 0.0005 | 0.0016 | 0.9588 | - |
541
+ | 12.0 | 79860 | - | - | - | 0.9583 |
542
+
543
+ </details>
544
+
545
+ ### Framework Versions
546
+ - Python: 3.10.12
547
+ - Sentence Transformers: 3.3.1
548
+ - Transformers: 4.47.1
549
+ - PyTorch: 2.2.2+cu121
550
+ - Accelerate: 1.2.1
551
+ - Datasets: 3.2.0
552
+ - Tokenizers: 0.21.0
553
+
554
+ ## Citation
555
+
556
+ ### BibTeX
557
+
558
+ #### Sentence Transformers
559
+ ```bibtex
560
+ @inproceedings{reimers-2019-sentence-bert,
561
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
562
+ author = "Reimers, Nils and Gurevych, Iryna",
563
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
564
+ month = "11",
565
+ year = "2019",
566
+ publisher = "Association for Computational Linguistics",
567
+ url = "https://arxiv.org/abs/1908.10084",
568
+ }
569
+ ```
570
+
571
+ <!--
572
+ ## Glossary
573
+
574
+ *Clearly define terms in order to be accessible across audiences.*
575
+ -->
576
+
577
+ <!--
578
+ ## Model Card Authors
579
+
580
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
581
+ -->
582
+
583
+ <!--
584
+ ## Model Card Contact
585
+
586
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
587
+ -->
config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
3
+ "architectures": [
4
+ "XLMRobertaModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "classifier_dropout": null,
9
+ "eos_token_id": 2,
10
+ "gradient_checkpointing": false,
11
+ "hidden_act": "gelu",
12
+ "hidden_dropout_prob": 0.1,
13
+ "hidden_size": 768,
14
+ "initializer_range": 0.02,
15
+ "intermediate_size": 3072,
16
+ "layer_norm_eps": 1e-05,
17
+ "max_position_embeddings": 514,
18
+ "model_type": "xlm-roberta",
19
+ "num_attention_heads": 12,
20
+ "num_hidden_layers": 12,
21
+ "output_past": true,
22
+ "pad_token_id": 1,
23
+ "position_embedding_type": "absolute",
24
+ "torch_dtype": "float32",
25
+ "transformers_version": "4.47.1",
26
+ "type_vocab_size": 1,
27
+ "use_cache": true,
28
+ "vocab_size": 250002
29
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.3.1",
4
+ "transformers": "4.47.1",
5
+ "pytorch": "2.2.2+cu121"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": "cosine"
10
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:584fa35e056a7838286e58289f1257192d84cd7ffec48c0bf2eb2c1dc14ef8cf
3
+ size 1112197096
modules.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "idx": 0,
4
+ "name": "0",
5
+ "path": "",
6
+ "type": "sentence_transformers.models.Transformer"
7
+ },
8
+ {
9
+ "idx": 1,
10
+ "name": "1",
11
+ "path": "1_Pooling",
12
+ "type": "sentence_transformers.models.Pooling"
13
+ }
14
+ ]
sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 128,
3
+ "do_lower_case": false
4
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "cls_token": {
10
+ "content": "<s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "eos_token": {
17
+ "content": "</s>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "mask_token": {
24
+ "content": "<mask>",
25
+ "lstrip": true,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "pad_token": {
31
+ "content": "<pad>",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ },
37
+ "sep_token": {
38
+ "content": "</s>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false
43
+ },
44
+ "unk_token": {
45
+ "content": "<unk>",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false
50
+ }
51
+ }
tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cad551d5600a84242d0973327029452a1e3672ba6313c2a3c3d69c4310e12719
3
+ size 17082987
tokenizer_config.json ADDED
@@ -0,0 +1,62 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<s>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "<pad>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "</s>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "250001": {
36
+ "content": "<mask>",
37
+ "lstrip": true,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "bos_token": "<s>",
45
+ "clean_up_tokenization_spaces": false,
46
+ "cls_token": "<s>",
47
+ "eos_token": "</s>",
48
+ "extra_special_tokens": {},
49
+ "mask_token": "<mask>",
50
+ "max_length": 128,
51
+ "model_max_length": 128,
52
+ "pad_to_multiple_of": null,
53
+ "pad_token": "<pad>",
54
+ "pad_token_type_id": 0,
55
+ "padding_side": "right",
56
+ "sep_token": "</s>",
57
+ "stride": 0,
58
+ "tokenizer_class": "XLMRobertaTokenizer",
59
+ "truncation_side": "right",
60
+ "truncation_strategy": "longest_first",
61
+ "unk_token": "<unk>"
62
+ }