Upload 12 files

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 1024,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -0,0 +1,127 @@
+---
+library_name: sentence-transformers
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- transformers
+
+---
+
+# {MODEL_NAME}
+
+This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
+
+<!--- Describe your model here -->
+
+## Usage (Sentence-Transformers)
+
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+
+```
+pip install -U sentence-transformers
+```
+
+Then you can use the model like this:
+
+```python
+from sentence_transformers import SentenceTransformer
+sentences = ["This is an example sentence", "Each sentence is converted"]
+
+model = SentenceTransformer('{MODEL_NAME}')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+
+
+## Usage (HuggingFace Transformers)
+Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
+
+```python
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+
+def cls_pooling(model_output, attention_mask):
+    return model_output[0][:,0]
+
+
+# Sentences we want sentence embeddings for
+sentences = ['This is an example sentence', 'Each sentence is converted']
+
+# Load model from HuggingFace Hub
+tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}')
+model = AutoModel.from_pretrained('{MODEL_NAME}')
+
+# Tokenize sentences
+encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
+
+# Compute token embeddings
+with torch.no_grad():
+    model_output = model(**encoded_input)
+
+# Perform pooling. In this case, cls pooling.
+sentence_embeddings = cls_pooling(model_output, encoded_input['attention_mask'])
+
+print("Sentence embeddings:")
+print(sentence_embeddings)
+```
+
+
+
+## Evaluation Results
+
+<!--- Describe how your model was evaluated -->
+
+For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME})
+
+
+## Training
+The model was trained with the parameters:
+
+**DataLoader**:
+
+`torch.utils.data.dataloader.DataLoader` of length 373 with parameters:
+```
+{'batch_size': 8, 'sampler': 'torch.utils.data.sampler.SequentialSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
+```
+
+**Loss**:
+
+`sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss` with parameters:
+  ```
+  {'scale': 20.0, 'similarity_fct': 'cos_sim'}
+  ```
+
+Parameters of the fit()-Method:
+```
+{
+    "epochs": 2,
+    "evaluation_steps": 50,
+    "evaluator": "sentence_transformers.evaluation.InformationRetrievalEvaluator.InformationRetrievalEvaluator",
+    "max_grad_norm": 1,
+    "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
+    "optimizer_params": {
+        "lr": 2e-05
+    },
+    "scheduler": "WarmupLinear",
+    "steps_per_epoch": null,
+    "warmup_steps": 74,
+    "weight_decay": 0.01
+}
+```
+
+
+## Full Model Architecture
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+)
+```
+
+## Citing & Authors
+
+<!--- Describe where people can find more information -->

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "mixedbread-ai/mxbai-embed-large-v1",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,9 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.5.1",
+    "transformers": "4.37.0",
+    "pytorch": "2.1.0+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

eval/Information-Retrieval_evaluation_results.csv

@@ -0,0 +1,19 @@
+epoch,steps,cos_sim-Accuracy@1,cos_sim-Accuracy@3,cos_sim-Accuracy@5,cos_sim-Accuracy@10,cos_sim-Precision@1,cos_sim-Recall@1,cos_sim-Precision@3,cos_sim-Recall@3,cos_sim-Precision@5,cos_sim-Recall@5,cos_sim-Precision@10,cos_sim-Recall@10,cos_sim-MRR@10,cos_sim-NDCG@10,cos_sim-MAP@100,dot_score-Accuracy@1,dot_score-Accuracy@3,dot_score-Accuracy@5,dot_score-Accuracy@10,dot_score-Precision@1,dot_score-Recall@1,dot_score-Precision@3,dot_score-Recall@3,dot_score-Precision@5,dot_score-Recall@5,dot_score-Precision@10,dot_score-Recall@10,dot_score-MRR@10,dot_score-NDCG@10,dot_score-MAP@100
+0,50,0.5933014354066986,0.6997607655502392,0.7320574162679426,0.7739234449760766,0.5933014354066986,0.5933014354066986,0.2332535885167464,0.6997607655502392,0.1464114832535885,0.7320574162679426,0.07739234449760764,0.7739234449760766,0.6546850079744815,0.683496862521924,0.6618926793077029,0.5753588516746412,0.6854066985645934,0.7177033492822966,0.7655502392344498,0.5753588516746412,0.5753588516746412,0.2284688995215311,0.6854066985645934,0.1435406698564593,0.7177033492822966,0.07655502392344496,0.7655502392344498,0.6388447444368495,0.6692917468093779,0.6461697816738289
+0,50,0.6016746411483254,0.7009569377990431,0.7368421052631579,0.7727272727272727,0.6016746411483254,0.6016746411483254,0.23365231259968103,0.7009569377990431,0.14736842105263157,0.7368421052631579,0.07727272727272727,0.7727272727272727,0.6604010025062659,0.6875997841847005,0.6678437293574607,0.5574162679425837,0.6770334928229665,0.715311004784689,0.7535885167464115,0.5574162679425837,0.5574162679425837,0.22567783094098887,0.6770334928229665,0.14306220095693778,0.715311004784689,0.07535885167464115,0.7535885167464115,0.6262588288904077,0.657269109230626,0.6345644058844592
+0,50,0.5789473684210527,0.6794258373205742,0.7081339712918661,0.7547846889952153,0.5789473684210527,0.5789473684210527,0.22647527910685805,0.6794258373205742,0.1416267942583732,0.7081339712918661,0.07547846889952152,0.7547846889952153,0.6379025214551528,0.666036330870378,0.6453389704062112,0.5370813397129187,0.6543062200956937,0.687799043062201,0.7404306220095693,0.5370813397129187,0.5370813397129187,0.21810207336523124,0.6543062200956937,0.1375598086124402,0.687799043062201,0.07404306220095694,0.7404306220095693,0.6055921052631577,0.6381297265724771,0.6138585262758153
+0,100,0.6172248803827751,0.7272727272727273,0.7583732057416268,0.7966507177033493,0.6172248803827751,0.6172248803827751,0.24242424242424246,0.7272727272727273,0.15167464114832535,0.7583732057416268,0.07966507177033492,0.7966507177033493,0.6775048416495786,0.7063652023258369,0.6837775853011498,0.5921052631578947,0.6985645933014354,0.7380382775119617,0.7894736842105263,0.5921052631578947,0.5921052631578947,0.2328548644338118,0.6985645933014354,0.14760765550239233,0.7380382775119617,0.07894736842105263,0.7894736842105263,0.6577214817346393,0.6894882032892604,0.6641206958776411
+0,150,0.6052631578947368,0.7200956937799043,0.7440191387559809,0.7954545454545454,0.6052631578947368,0.6052631578947368,0.24003189792663476,0.7200956937799043,0.14880382775119616,0.7440191387559809,0.07954545454545454,0.7954545454545454,0.6702907837776259,0.7004956444460179,0.6770299880628449,0.5861244019138756,0.7045454545454546,0.7356459330143541,0.7751196172248804,0.5861244019138756,0.5861244019138756,0.23484848484848486,0.7045454545454546,0.1471291866028708,0.7356459330143541,0.07751196172248803,0.7751196172248804,0.651657078301815,0.6816353310366399,0.659842050139608
+0,200,0.6160287081339713,0.7320574162679426,0.7643540669856459,0.8038277511961722,0.6160287081339713,0.6160287081339713,0.24401913875598086,0.7320574162679426,0.15287081339712916,0.7643540669856459,0.08038277511961721,0.8038277511961722,0.682614205969469,0.7121652411453161,0.6894657566488197,0.5813397129186603,0.7188995215311005,0.7511961722488039,0.7930622009569378,0.5813397129186603,0.5813397129186603,0.23963317384370014,0.7188995215311005,0.15023923444976073,0.7511961722488039,0.07930622009569376,0.7930622009569378,0.6560140882509302,0.6893578586487552,0.663050928016724
+0,250,0.6196172248803827,0.7368421052631579,0.7799043062200957,0.812200956937799,0.6196172248803827,0.6196172248803827,0.24561403508771928,0.7368421052631579,0.1559808612440191,0.7799043062200957,0.08122009569377991,0.812200956937799,0.688214380648591,0.7184866095328476,0.6944297871089213,0.5669856459330144,0.7057416267942583,0.7404306220095693,0.7954545454545454,0.5669856459330144,0.5669856459330144,0.23524720893141945,0.7057416267942583,0.14808612440191385,0.7404306220095693,0.07954545454545454,0.7954545454545454,0.6453187893977366,0.681713789479489,0.651955653851378
+0,300,0.6363636363636364,0.7380382775119617,0.7679425837320574,0.812200956937799,0.6363636363636364,0.6363636363636364,0.2460127591706539,0.7380382775119617,0.15358851674641147,0.7679425837320574,0.0812200956937799,0.812200956937799,0.6953054985949725,0.7234759338739174,0.7022979866019123,0.6052631578947368,0.7188995215311005,0.7535885167464115,0.7930622009569378,0.6052631578947368,0.6052631578947368,0.23963317384370014,0.7188995215311005,0.15071770334928228,0.7535885167464115,0.07930622009569378,0.7930622009569378,0.6711997797524112,0.7008100713451701,0.678895306814488
+0,350,0.6267942583732058,0.7296650717703349,0.7691387559808612,0.8145933014354066,0.6267942583732058,0.6267942583732058,0.24322169059011162,0.7296650717703349,0.15382775119617223,0.7691387559808612,0.08145933014354066,0.8145933014354066,0.6897940874914555,0.7198400722036162,0.6963184094494127,0.5980861244019139,0.7057416267942583,0.7404306220095693,0.8038277511961722,0.5980861244019139,0.5980861244019139,0.23524720893141945,0.7057416267942583,0.14808612440191385,0.7404306220095693,0.08038277511961721,0.8038277511961722,0.6638437950937951,0.6972702093262709,0.6704041884622407
+0,-1,0.6136363636363636,0.7188995215311005,0.7607655502392344,0.8169856459330144,0.6136363636363636,0.6136363636363636,0.23963317384370014,0.7188995215311005,0.15215311004784687,0.7607655502392344,0.08169856459330141,0.8169856459330144,0.6779980253664464,0.7112502378067767,0.6840140707619233,0.5885167464114832,0.6973684210526315,0.7356459330143541,0.8002392344497608,0.5885167464114832,0.5885167464114832,0.23245614035087717,0.6973684210526315,0.1471291866028708,0.7356459330143541,0.08002392344497607,0.8002392344497608,0.6565348029163816,0.6908359041417305,0.6630275229810563
+1,50,0.6399521531100478,0.7523923444976076,0.7906698564593302,0.8277511961722488,0.6399521531100478,0.6399521531100478,0.25079744816586924,0.7523923444976076,0.15813397129186602,0.7906698564593302,0.08277511961722489,0.8277511961722488,0.7046774132300448,0.7345891388548581,0.7111919408825712,0.6136363636363636,0.7200956937799043,0.7559808612440191,0.8110047846889952,0.6136363636363636,0.6136363636363636,0.24003189792663476,0.7200956937799043,0.1511961722488038,0.7559808612440191,0.08110047846889952,0.8110047846889952,0.6777991379965063,0.7098285796205315,0.6846442887172792
+1,100,0.65311004784689,0.7488038277511961,0.784688995215311,0.8169856459330144,0.65311004784689,0.65311004784689,0.2496012759170654,0.7488038277511961,0.15693779904306218,0.784688995215311,0.08169856459330141,0.8169856459330144,0.7092119503303709,0.7354379712077865,0.7157366252451849,0.6255980861244019,0.7344497607655502,0.7655502392344498,0.8133971291866029,0.6255980861244019,0.6255980861244019,0.2448165869218501,0.7344497607655502,0.15311004784688995,0.7655502392344498,0.08133971291866028,0.8133971291866029,0.6881920710868079,0.7184125944959279,0.6946124958410717
+1,150,0.6411483253588517,0.7404306220095693,0.7811004784688995,0.8205741626794258,0.6411483253588517,0.6411483253588517,0.2468102073365231,0.7404306220095693,0.1562200956937799,0.7811004784688995,0.08205741626794258,0.8205741626794258,0.7015711627553735,0.7303542220437288,0.707838426398782,0.6208133971291866,0.7296650717703349,0.7583732057416268,0.8157894736842105,0.6208133971291866,0.6208133971291866,0.24322169059011162,0.7296650717703349,0.15167464114832535,0.7583732057416268,0.08157894736842106,0.8157894736842105,0.683975089238247,0.7155816585401292,0.6902476519071689
+1,200,0.638755980861244,0.7416267942583732,0.7751196172248804,0.8241626794258373,0.638755980861244,0.638755980861244,0.2472089314194577,0.7416267942583732,0.15502392344497606,0.7751196172248804,0.08241626794258372,0.8241626794258373,0.6994640958456749,0.7294660872798413,0.706028673257135,0.6196172248803827,0.7284688995215312,0.7679425837320574,0.8169856459330144,0.6196172248803827,0.6196172248803827,0.24282296650717702,0.7284688995215312,0.15358851674641147,0.7679425837320574,0.08169856459330144,0.8169856459330144,0.6838065808460546,0.715870298370102,0.6905641378624777
+1,250,0.6519138755980861,0.7452153110047847,0.7787081339712919,0.8253588516746412,0.6519138755980861,0.6519138755980861,0.24840510366826155,0.7452153110047847,0.15574162679425835,0.7787081339712919,0.08253588516746412,0.8253588516746412,0.7084073820915927,0.7365031932125676,0.7150210093229937,0.6255980861244019,0.7344497607655502,0.7667464114832536,0.8169856459330144,0.6255980861244019,0.6255980861244019,0.24481658692185007,0.7344497607655502,0.1533492822966507,0.7667464114832536,0.08169856459330144,0.8169856459330144,0.6891936280094174,0.7199762085297226,0.6959606484381059
+1,300,0.6495215311004785,0.7476076555023924,0.784688995215311,0.8229665071770335,0.6495215311004785,0.6495215311004785,0.24920255183413076,0.7476076555023924,0.15693779904306218,0.784688995215311,0.08229665071770334,0.8229665071770335,0.7072909546593756,0.735196573005543,0.7141970879766035,0.6267942583732058,0.7356459330143541,0.7751196172248804,0.8157894736842105,0.6267942583732058,0.6267942583732058,0.2452153110047847,0.7356459330143541,0.15502392344497606,0.7751196172248804,0.08157894736842106,0.8157894736842105,0.6910747512721199,0.7212896916867635,0.6978838677901712
+1,350,0.6543062200956937,0.757177033492823,0.784688995215311,0.8253588516746412,0.6543062200956937,0.6543062200956937,0.25239234449760767,0.757177033492823,0.15693779904306218,0.784688995215311,0.08253588516746412,0.8253588516746412,0.711998746867168,0.7393494756289931,0.7187389385391895,0.6196172248803827,0.7308612440191388,0.7739234449760766,0.812200956937799,0.6196172248803827,0.6196172248803827,0.24362041467304624,0.7308612440191388,0.15478468899521533,0.7739234449760766,0.0812200956937799,0.812200956937799,0.6863228146122881,0.7169398168020888,0.6934823050320625
+1,-1,0.6543062200956937,0.757177033492823,0.784688995215311,0.8229665071770335,0.6543062200956937,0.6543062200956937,0.25239234449760767,0.757177033492823,0.15693779904306218,0.784688995215311,0.08229665071770334,0.8229665071770335,0.711784195336827,0.7386822609348395,0.718739820073187,0.6196172248803827,0.7308612440191388,0.7751196172248804,0.812200956937799,0.6196172248803827,0.6196172248803827,0.24362041467304624,0.7308612440191388,0.15502392344497606,0.7751196172248804,0.0812200956937799,0.812200956937799,0.6863541429330902,0.7169770062474276,0.6934688811933988

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44f1d8527919a9f337045dc9370e71bc4603cb78ddd0cfe20cf034eda1ecef48
+size 1340612432

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}