Delete arq1thru3-finetuned-all-mpnet-jul-27

arq1thru3-finetuned-all-mpnet-jul-27/1_Pooling/config.json

@@ -1,7 +0,0 @@
-{
-  "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
-}

arq1thru3-finetuned-all-mpnet-jul-27/README.md

@@ -1,88 +0,0 @@
----
-pipeline_tag: sentence-similarity
-tags:
-- sentence-transformers
-- feature-extraction
-- sentence-similarity
-
----
-
-# {MODEL_NAME}
-
-This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 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)
-```
-
-
-
-## 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 870 with parameters:
-```
-{'batch_size': 16, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
-```
-
-**Loss**:
-
-`sentence_transformers.losses.CosineSimilarityLoss.CosineSimilarityLoss` 
-
-Parameters of the fit()-Method:
-```
-{
-    "epochs": 10,
-    "evaluation_steps": 0,
-    "evaluator": "sentence_transformers.evaluation.EmbeddingSimilarityEvaluator.EmbeddingSimilarityEvaluator",
-    "max_grad_norm": 1,
-    "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
-    "optimizer_params": {
-        "lr": 2e-05
-    },
-    "scheduler": "WarmupLinear",
-    "steps_per_epoch": null,
-    "warmup_steps": 870,
-    "weight_decay": 0.01
-}
-```
-
-
-## Full Model Architecture
-```
-SentenceTransformer(
-  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel 
-  (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})
-  (2): Normalize()
-)
-```
-
-## Citing & Authors
-
-<!--- Describe where people can find more information -->

arq1thru3-finetuned-all-mpnet-jul-27/config.json

@@ -1,24 +0,0 @@
-{
-  "_name_or_path": "/home/shea.durgin/.cache/torch/sentence_transformers/sentence-transformers_all-mpnet-base-v2/",
-  "architectures": [
-    "MPNetModel"
-  ],
-  "attention_probs_dropout_prob": 0.1,
-  "bos_token_id": 0,
-  "eos_token_id": 2,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.1,
-  "hidden_size": 768,
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "layer_norm_eps": 1e-05,
-  "max_position_embeddings": 514,
-  "model_type": "mpnet",
-  "num_attention_heads": 12,
-  "num_hidden_layers": 12,
-  "pad_token_id": 1,
-  "relative_attention_num_buckets": 32,
-  "torch_dtype": "float32",
-  "transformers_version": "4.27.4",
-  "vocab_size": 30527
-}

arq1thru3-finetuned-all-mpnet-jul-27/config_sentence_transformers.json

@@ -1,7 +0,0 @@
-{
-  "__version__": {
-    "sentence_transformers": "2.0.0",
-    "transformers": "4.6.1",
-    "pytorch": "1.8.1"
-  }
-}

arq1thru3-finetuned-all-mpnet-jul-27/eval/similarity_evaluation_results.csv

@@ -1,11 +0,0 @@
-epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman
-0,-1,0.4321461772218685,0.41115121214875444,0.45990001483672766,0.411151212154751,0.45905745272270226,0.41064821756888736,0.43214617337638445,0.41115121214875444
-1,-1,0.43516245644816287,0.4063511470057993,0.4685264022331696,0.40635101591292705,0.4680518463267778,0.4060915844447121,0.43516245301394063,0.4063511470057993
-2,-1,0.4482803580115485,0.41142131368566004,0.4834178839198377,0.4114213136916606,0.4826778225812374,0.41149996326516486,0.4482803596097107,0.41142131367965956
-3,-1,0.45211567020774257,0.40408640548677915,0.48501250608220714,0.40408640549267266,0.4846458205623765,0.40441457044900236,0.4521156733913541,0.40408653657971744
-4,-1,0.4479131268648339,0.3950822160333478,0.4810441126236694,0.39508221603911003,0.480416632194862,0.39498022615280526,0.4479131276516076,0.39508221602182336
-5,-1,0.4419252001262697,0.39051744254925125,0.4794230549676836,0.3905173114673084,0.4790365276357312,0.3903610465678447,0.44192520291396936,0.3905174425435556
-6,-1,0.44295744032161927,0.38496601838887096,0.479861121980147,0.38496601839448563,0.47961208537632083,0.38513613084493437,0.44295743619045685,0.38496601838887096
-7,-1,0.43438512931778,0.3751018764797458,0.46910559207484126,0.3751018764797458,0.46861062698239103,0.37468892967585204,0.4343851299101564,0.3751018764688041
-8,-1,0.4418029578605317,0.3792913984503816,0.47794939606415116,0.3792915703773857,0.4777654296725235,0.37932879962994553,0.4418029500245675,0.37929081280636007
-9,-1,0.4412656423379331,0.38120146682990985,0.4784195166149522,0.3812014464270963,0.4782542699404671,0.3810158556141353,0.44126564454201883,0.3812014668132305

arq1thru3-finetuned-all-mpnet-jul-27/modules.json

@@ -1,20 +0,0 @@
-[
-  {
-    "idx": 0,
-    "name": "0",
-    "path": "",
-    "type": "sentence_transformers.models.Transformer"
-  },
-  {
-    "idx": 1,
-    "name": "1",
-    "path": "1_Pooling",
-    "type": "sentence_transformers.models.Pooling"
-  },
-  {
-    "idx": 2,
-    "name": "2",
-    "path": "2_Normalize",
-    "type": "sentence_transformers.models.Normalize"
-  }
-]

arq1thru3-finetuned-all-mpnet-jul-27/pytorch_model.bin

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2b9fdcf796dcb15a25da7ad96d67bc4d5b5a46bd2fff138e17108d09c37fd5f8
-size 438016493

arq1thru3-finetuned-all-mpnet-jul-27/sentence_bert_config.json

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

arq1thru3-finetuned-all-mpnet-jul-27/special_tokens_map.json

@@ -1,15 +0,0 @@
-{
-  "bos_token": "<s>",
-  "cls_token": "<s>",
-  "eos_token": "</s>",
-  "mask_token": {
-    "content": "<mask>",
-    "lstrip": true,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "pad_token": "<pad>",
-  "sep_token": "</s>",
-  "unk_token": "[UNK]"
-}

arq1thru3-finetuned-all-mpnet-jul-27/tokenizer_config.json

@@ -1,15 +0,0 @@
-{
-  "bos_token": "<s>",
-  "cls_token": "<s>",
-  "do_lower_case": true,
-  "eos_token": "</s>",
-  "mask_token": "<mask>",
-  "model_max_length": 512,
-  "pad_token": "<pad>",
-  "sep_token": "</s>",
-  "special_tokens_map_file": null,
-  "strip_accents": null,
-  "tokenize_chinese_chars": true,
-  "tokenizer_class": "MPNetTokenizer",
-  "unk_token": "[UNK]"
-}