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Commit
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.gitignore ADDED
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+ checkpoint-*/
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - conll2003
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+ model_index:
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+ - name: distilbert-base-uncased-squad2-with-ner-with-neg-with-repeat
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+ results:
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+ - task:
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+ name: Question Answering
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+ type: question-answering
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+ dataset:
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+ name: conll2003
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+ type: conll2003
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+ args: conll2003
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilbert-base-uncased-squad2-with-ner-with-neg-with-repeat
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+
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+ This model is a fine-tuned version of [twmkn9/distilbert-base-uncased-squad2](https://huggingface.co/twmkn9/distilbert-base-uncased-squad2) on the conll2003 dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.8.2
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+ - Pytorch 1.8.1+cu111
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+ - Datasets 1.8.0
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+ - Tokenizers 0.10.3
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+ {
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+ "train_samples_per_second": 74.746,
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+ "train_steps_per_second": 4.672
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+ }
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+ {
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+ "_name_or_path": "twmkn9/distilbert-base-uncased-squad2",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForQuestionAnswering"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "sinusoidal_pos_embds": false,
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+ "tie_weights_": true,
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+ "transformers_version": "4.8.2",
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+ "vocab_size": 30522
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+ }
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+ Training dataset length:
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+ 62808
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+ Validation dataset length:
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+ 13000
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+ Test dataset length:
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+ 13812
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