96abhishekarora commited on
Commit
78b8875
1 Parent(s): efb35e9

Modified validation and training for linktransformer model

Browse files
.gitattributes CHANGED
@@ -37,3 +37,5 @@ pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
@@ -14,7 +14,7 @@ tags:
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  # dell-research-harvard/lt-un-data-fine-fine-multi
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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.
19
  Notwithstanding that, it can be used for any sentence similarity task within the sentence-transformers framework as well.
20
  It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
@@ -101,7 +101,7 @@ The model was trained with the parameters:
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  **DataLoader**:
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- `torch.utils.data.dataloader.DataLoader` of length 306 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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  ```
@@ -114,16 +114,16 @@ 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": 3060,
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  "evaluator": "sentence_transformers.evaluation.SequentialEvaluator.SequentialEvaluator",
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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": 30600,
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  "weight_decay": 0.01
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  }
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  ```
@@ -133,10 +133,20 @@ Parameters of the fit()-Method:
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  LinkTransformer(
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  (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
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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})
137
  )
138
  ```
139
 
140
  ## Citing & Authors
141
 
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- <!--- Describe where people can find more information -->
 
 
 
 
 
 
 
 
 
 
 
14
 
15
  # dell-research-harvard/lt-un-data-fine-fine-multi
16
 
17
+ 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.
18
  It is designed for quick and easy record linkage (entity-matching) through the LinkTransformer package. The tasks include clustering, deduplication, linking, aggregation and more.
19
  Notwithstanding that, it can be used for any sentence similarity task within the sentence-transformers framework as well.
20
  It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
101
 
102
  **DataLoader**:
103
 
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+ `torch.utils.data.dataloader.DataLoader` of length 304 with parameters:
105
  ```
106
  {'batch_size': 64, 'sampler': 'torch.utils.data.dataloader._InfiniteConstantSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
107
  ```
 
114
  ```
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  {
116
  "epochs": 100,
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  "evaluator": "sentence_transformers.evaluation.SequentialEvaluator.SequentialEvaluator",
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+ "warmup_steps": 30400,
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  "weight_decay": 0.01
128
  }
129
  ```
 
133
 
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  LinkTransformer(
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  (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: XLMRobertaModel
136
+ (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})
137
  )
138
  ```
139
 
140
  ## Citing & Authors
141
 
142
+ ```
143
+ @misc{arora2023linktransformer,
144
+ 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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