96abhishekarora
commited on
Commit
•
ba6f1fe
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Parent(s):
e704e62
Modified validation and training for linktransformer model
Browse files- .gitattributes +2 -0
- 1_Pooling/config.json +3 -1
- LT_training_config.json +4 -2
- README.md +15 -5
- config.json +2 -2
- model.safetensors +3 -0
- special_tokens_map.json +42 -6
- tokenizer_config.json +57 -0
.gitattributes
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@@ -36,3 +36,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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.git/lfs/objects/ac/e3/ace3c71b97a96f01b2feceec24958b690700ea37ad188af305b32ef472101546 filter=lfs diff=lfs merge=lfs -text
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.git/lfs/objects/a1/ca/a1caf77aeeb33f22a280e7dd98da99969ecbc0b510530aacd240d85af85b27f5 filter=lfs diff=lfs merge=lfs -text
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pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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.git/lfs/objects/ac/e3/ace3c71b97a96f01b2feceec24958b690700ea37ad188af305b32ef472101546 filter=lfs diff=lfs merge=lfs -text
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.git/lfs/objects/a1/ca/a1caf77aeeb33f22a280e7dd98da99969ecbc0b510530aacd240d85af85b27f5 filter=lfs diff=lfs merge=lfs -text
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model.safetensors filter=lfs diff=lfs merge=lfs -text
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.git/lfs/objects/29/5e/295e70b58fbf265c9bdad1a24cf9f099be0ff2381e7ade96ccf9e457aafcc36e filter=lfs diff=lfs merge=lfs -text
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1_Pooling/config.json
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false
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}
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false
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}
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LT_training_config.json
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"train_batch_size": 64,
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"num_epochs": 100,
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"warm_up_perc": 1,
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"learning_rate": 2e-
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"val_perc": 0.2,
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"wandb_names": {
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"project": "linkage",
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},
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"add_pooling_layer": false,
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"large_val": true,
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"eval_steps_perc": 0.
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"test_at_end": true,
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"save_val_test_pickles": true,
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"val_query_prop": 0.5,
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"eval_type": "retrieval",
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"training_dataset": "dataframe",
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"base_model_path": "multi-qa-mpnet-base-dot-v1",
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"train_batch_size": 64,
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"num_epochs": 100,
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"warm_up_perc": 1,
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"learning_rate": 2e-05,
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"loss_type": "supcon",
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"val_perc": 0.2,
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"wandb_names": {
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"project": "linkage",
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},
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"add_pooling_layer": false,
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"large_val": true,
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"eval_steps_perc": 0.5,
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"test_at_end": true,
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"save_val_test_pickles": true,
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"val_query_prop": 0.5,
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"loss_params": {},
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"eval_type": "retrieval",
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"training_dataset": "dataframe",
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"base_model_path": "multi-qa-mpnet-base-dot-v1",
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README.md
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# dell-research-harvard/lt-un-data-fine-fine-en
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This is a [LinkTransformer](https://github.
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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.
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```
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{
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"epochs": 100,
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"evaluation_steps":
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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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"optimizer_params": {
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"lr": 2e-
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},
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"scheduler": "WarmupLinear",
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"steps_per_epoch": null,
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LinkTransformer(
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(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel
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(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
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)
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```
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## Citing & Authors
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-
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# dell-research-harvard/lt-un-data-fine-fine-en
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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.
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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.
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```
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{
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"epochs": 100,
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"evaluation_steps": 75,
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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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"optimizer_params": {
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"lr": 2e-05
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},
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"scheduler": "WarmupLinear",
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"steps_per_epoch": null,
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LinkTransformer(
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(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: MPNetModel
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(1): Pooling({'word_embedding_dimension': 768, '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})
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)
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```
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## Citing & Authors
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```
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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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config.json
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{
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"_name_or_path": "models/linkage_un_data_en_fine_fine
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"architectures": [
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"MPNetModel"
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],
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"pad_token_id": 1,
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"relative_attention_num_buckets": 32,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"vocab_size": 30527
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}
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{
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"_name_or_path": "models/linkage_un_data_en_fine_fine",
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"architectures": [
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"MPNetModel"
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"pad_token_id": 1,
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"torch_dtype": "float32",
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"transformers_version": "4.35.1",
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"vocab_size": 30527
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fbd246fa5fe8529451aee46397c8e583166d5588080b036919b0641d5b8751a5
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size 437967672
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special_tokens_map.json
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{
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tokenizer_config.json
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