96abhishekarora commited on
Commit
5196430
1 Parent(s): b33b65a

Add new LinkTransformer model.

Browse files
.gitattributes CHANGED
@@ -35,3 +35,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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1_Pooling/config.json CHANGED
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LT_training_config.json CHANGED
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README.md CHANGED
@@ -11,7 +11,7 @@ tags:
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  # dell-research-harvard/lt-mexicantrade4748
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- This is a [LinkTransformer](https://github.com/dell-research-harvard/linktransformer) model. At its core this model this is a sentence transformer model [sentence-transformers](https://www.SBERT.net) model- it just wraps around the class.
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  It is designed for quick and easy record linkage (entity-matching) through the LinkTransformer package. The tasks include clustering, deduplication, linking, aggregation and more.
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  Notwithstanding that, it can be used for any sentence similarity task within the sentence-transformers framework as well.
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  It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
@@ -94,7 +94,7 @@ The model was trained with the parameters:
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  **DataLoader**:
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- `torch.utils.data.dataloader.DataLoader` of length 50 with parameters:
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  ```
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  {'batch_size': 64, 'sampler': 'torch.utils.data.dataloader._InfiniteConstantSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
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  ```
@@ -106,17 +106,17 @@ The model was trained with the parameters:
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  Parameters of the fit()-Method:
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  ```
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  {
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- "epochs": 100,
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- "evaluation_steps": 500,
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  "evaluator": "sentence_transformers.evaluation.SequentialEvaluator.SequentialEvaluator",
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  "weight_decay": 0.01
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  }
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  ```
@@ -126,10 +126,20 @@ Parameters of the fit()-Method:
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  LinkTransformer(
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  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
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- (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})
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  )
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  ```
132
 
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  ## Citing & Authors
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- <!--- Describe where people can find more information -->
 
 
 
 
 
 
 
 
 
 
 
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  # dell-research-harvard/lt-mexicantrade4748
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+ This is a [LinkTransformer](https://linktransformer.github.io/) model. At its core this model this is a sentence transformer model [sentence-transformers](https://www.SBERT.net) model- it just wraps around the class.
15
  It is designed for quick and easy record linkage (entity-matching) through the LinkTransformer package. The tasks include clustering, deduplication, linking, aggregation and more.
16
  Notwithstanding that, it can be used for any sentence similarity task within the sentence-transformers framework as well.
17
  It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
94
 
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  **DataLoader**:
96
 
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+ `torch.utils.data.dataloader.DataLoader` of length 67 with parameters:
98
  ```
99
  {'batch_size': 64, 'sampler': 'torch.utils.data.dataloader._InfiniteConstantSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
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  ```
 
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  Parameters of the fit()-Method:
107
  ```
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  {
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+ "epochs": 200,
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+ "evaluation_steps": 34,
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  "evaluator": "sentence_transformers.evaluation.SequentialEvaluator.SequentialEvaluator",
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  "max_grad_norm": 1,
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  "optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
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  "steps_per_epoch": null,
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+ "warmup_steps": 13400,
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  "weight_decay": 0.01
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  }
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  ```
 
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  LinkTransformer(
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  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel
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+ (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})
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  )
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  ```
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  ## Citing & Authors
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135
+ ```
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+ @misc{arora2023linktransformer,
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+ title={LinkTransformer: A Unified Package for Record Linkage with Transformer Language Models},
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+ author={Abhishek Arora and Melissa Dell},
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+ year={2023},
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+ eprint={2309.00789},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+
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+ ```
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