add model

.gitignore

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+checkpoint-*/

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+model_index:
+- name: distilbert-base-uncased-squad2-with-ner-with-neg-with-multi
+  results:
+  - task:
+      name: Question Answering
+      type: question-answering
+    dataset:
+      name: conll2003
+      type: conll2003
+      args: conll2003
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distilbert-base-uncased-squad2-with-ner-with-neg-with-multi
+
+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.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.8.2
+- Pytorch 1.8.1+cu111
+- Datasets 1.8.0
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "twmkn9/distilbert-base-uncased-squad2",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForQuestionAnswering"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "eos_token_ids": null,
+  "hidden_dim": 3072,
+  "initializer_range": 0.02,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.8.2",
+  "vocab_size": 30522
+}

log.log

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+Training dataset length: 
+75365
+Validation dataset length: 
+18000
+Test dataset length: 
+17966
+Current eval performance: 
+Evaluate results: 
+{'eval_exact': 61.166666666666664, 'eval_f1': 62.85259551738643, 'eval_total': 18000, 'eval_HasAns_exact': 29.12621359223301, 'eval_HasAns_f1': 34.38743400016661, 'eval_HasAns_total': 5768, 'eval_NoAns_exact': 76.2753433616743, 'eval_NoAns_f1': 76.2753433616743, 'eval_NoAns_total': 12232, 'eval_best_exact': 67.96666666666667, 'eval_best_exact_thresh': 0.0, 'eval_best_f1': 67.98520126170126, 'eval_best_f1_thresh': 0.0, 'eval_samples': 18000}
+Predict results: 
+{'test_exact': 62.00601135478125, 'test_f1': 63.80738510177029, 'test_total': 17966, 'test_HasAns_exact': 27.75644541963796, 'test_HasAns_f1': 33.67406852046233, 'test_HasAns_total': 5469, 'test_NoAns_exact': 76.99447867488198, 'test_NoAns_f1': 76.99447867488198, 'test_NoAns_total': 12497, 'test_best_exact': 69.59812980073472, 'test_best_exact_thresh': 0.0, 'test_best_f1': 69.61402402068104, 'test_best_f1_thresh': 0.0, 'predict_samples': 17966}
+Best trial: 
+BestRun(run_id='6', objective=96.43176121181548, hyperparameters={'learning_rate': 5e-05, 'num_train_epochs': 4, 'per_device_train_batch_size': 16, 'warmup_steps': 0})

pytorch_model.bin

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special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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training_args.bin

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