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clincolnoz
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MoreSexistBERT-edos

Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
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Files changed (14) hide show
  1. README.md +96 -0
  2. added_tokens.json +258 -0
  3. all_results.json +20 -0
  4. config.json +35 -0
  5. eval_results.json +15 -0
  6. predict_results_None.txt +4001 -0
  7. pytorch_model.bin +3 -0
  8. special_tokens_map.json +7 -0
  9. tokenizer.json +0 -0
  10. tokenizer_config.json +13 -0
  11. train_results.json +8 -0
  12. trainer_state.json +106 -0
  13. training_args.bin +3 -0
  14. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: final-lr2e-5-bs16
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+ results: []
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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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+ # final-lr2e-5-bs16
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+
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+ This model is a fine-tuned version of [clincolnoz/MoreSexistBERT](https://huggingface.co/clincolnoz/MoreSexistBERT) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3337
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+ - F1 Macro: 0.8461
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+ - F1 Weighted: 0.8868
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+ - F1: 0.7671
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+ - Accuracy: 0.8868
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+ - Confusion Matrix: [[2801 229]
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+ [ 224 746]]
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+ - Confusion Matrix Norm: [[0.92442244 0.07557756]
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+ [0.23092784 0.76907216]]
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+ - Classification Report: precision recall f1-score support
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+ 0 0.925950 0.924422 0.925186 3030.00000
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+ 1 0.765128 0.769072 0.767095 970.00000
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+ accuracy 0.886750 0.886750 0.886750 0.88675
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+ macro avg 0.845539 0.846747 0.846140 4000.00000
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+ weighted avg 0.886951 0.886750 0.886849 4000.00000
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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: 12345
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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: 3.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | F1 | Accuracy | Confusion Matrix | Confusion Matrix Norm | Classification Report |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:------:|:--------:|:--------------------------:|:--------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
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+ | 0.3196 | 1.0 | 1000 | 0.2973 | 0.8423 | 0.8871 | 0.7554 | 0.8902 | [[2883 147]
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+ [ 292 678]] | [[0.95148515 0.04851485]
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+ [0.30103093 0.69896907]] | precision recall f1-score support
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+ 0 0.908031 0.951485 0.929251 3030.00000
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+ 1 0.821818 0.698969 0.755432 970.00000
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+ accuracy 0.890250 0.890250 0.890250 0.89025
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+ macro avg 0.864925 0.825227 0.842341 4000.00000
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+ weighted avg 0.887125 0.890250 0.887100 4000.00000 |
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+ | 0.2447 | 2.0 | 2000 | 0.3277 | 0.8447 | 0.8872 | 0.7623 | 0.8885 | [[2839 191]
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+ [ 255 715]] | [[0.9369637 0.0630363]
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+ [0.2628866 0.7371134]] | precision recall f1-score support
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+ 0 0.917582 0.936964 0.927172 3030.0000
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+ 1 0.789183 0.737113 0.762260 970.0000
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+ accuracy 0.888500 0.888500 0.888500 0.8885
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+ macro avg 0.853383 0.837039 0.844716 4000.0000
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+ weighted avg 0.886446 0.888500 0.887181 4000.0000 |
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+ | 0.2037 | 3.0 | 3000 | 0.3337 | 0.8461 | 0.8868 | 0.7671 | 0.8868 | [[2801 229]
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+ [ 224 746]] | [[0.92442244 0.07557756]
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+ [0.23092784 0.76907216]] | precision recall f1-score support
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+ 0 0.925950 0.924422 0.925186 3030.00000
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+ 1 0.765128 0.769072 0.767095 970.00000
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+ accuracy 0.886750 0.886750 0.886750 0.88675
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+ macro avg 0.845539 0.846747 0.846140 4000.00000
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+ weighted avg 0.886951 0.886750 0.886849 4000.00000 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.0.dev0
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+ - Pytorch 1.13.1+cu117
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2
added_tokens.json ADDED
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+ "isnt": 30562,
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+ "i’ll": 30675,
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+ "i’m": 30668,
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+ "let’s": 30646,
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+ "lmao": 30660,
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+ "ltr": 30745,
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+ "man's": 30773,
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+ "manlet": 30713,
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+ "masculinity": 30563,
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+ "memes": 30658,
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+ "mentality": 30630,
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+ "oppressed": 30663,
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+ "overweight": 30709,
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+ "paternity": 30531,
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+ "patriarchy": 30538,
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+ "picky": 30597,
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+ "pussies": 30751,
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+ "rapes": 30575,
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+ }
all_results.json ADDED
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+ {
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+ "epoch": 3.0,
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+ "eval_accuracy": 0.88675,
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+ "eval_classification_report": " precision recall f1-score support\n0 0.925950 0.924422 0.925186 3030.00000\n1 0.765128 0.769072 0.767095 970.00000\naccuracy 0.886750 0.886750 0.886750 0.88675\nmacro avg 0.845539 0.846747 0.846140 4000.00000\nweighted avg 0.886951 0.886750 0.886849 4000.00000",
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+ "eval_confusion_matrix": "[[2801 229]\n [ 224 746]]",
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+ "eval_confusion_matrix_norm": "[[0.92442244 0.07557756]\n [0.23092784 0.76907216]]",
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+ "eval_f1": 0.7670951156812339,
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+ "eval_f1_macro": 0.8461404562716657,
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+ "eval_f1_weighted": 0.886848806675738,
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+ "eval_loss": 0.33370330929756165,
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+ "eval_runtime": 9.6197,
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+ "eval_samples": 4000,
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+ "eval_samples_per_second": 415.813,
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+ "eval_steps_per_second": 25.988,
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+ "train_loss": 0.276834108988444,
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+ "train_runtime": 437.8665,
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+ "train_samples": 16000,
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+ "train_samples_per_second": 109.622,
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+ "train_steps_per_second": 6.851
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+ }
config.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "_name_or_path": "clincolnoz/MoreSexistBERT",
3
+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "not sexist",
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+ "1": "sexist"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "not sexist": 0,
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+ "sexist": 1
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.27.0.dev0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30778
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+ }
eval_results.json ADDED
@@ -0,0 +1,15 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
2
+ "epoch": 3.0,
3
+ "eval_accuracy": 0.88675,
4
+ "eval_classification_report": " precision recall f1-score support\n0 0.925950 0.924422 0.925186 3030.00000\n1 0.765128 0.769072 0.767095 970.00000\naccuracy 0.886750 0.886750 0.886750 0.88675\nmacro avg 0.845539 0.846747 0.846140 4000.00000\nweighted avg 0.886951 0.886750 0.886849 4000.00000",
5
+ "eval_confusion_matrix": "[[2801 229]\n [ 224 746]]",
6
+ "eval_confusion_matrix_norm": "[[0.92442244 0.07557756]\n [0.23092784 0.76907216]]",
7
+ "eval_f1": 0.7670951156812339,
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+ "eval_f1_macro": 0.8461404562716657,
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+ "eval_f1_weighted": 0.886848806675738,
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+ "eval_loss": 0.33370330929756165,
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+ "eval_runtime": 9.6197,
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+ "eval_samples": 4000,
13
+ "eval_samples_per_second": 415.813,
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+ "eval_steps_per_second": 25.988
15
+ }
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1241
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1302
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1307
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1308
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1311
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1314
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1315
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1324
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1325
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1327
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1332
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1334
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1335
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1336
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1337
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1341
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1342
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1349
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1351
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1361
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1362
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1368
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1369
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1370
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1371
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1391
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1397
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1401
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1402
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1403
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1404
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1407
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1408
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1411
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1415
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1416
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1417
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1418
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1419
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1420
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1421
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1422
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1423
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1424
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1425
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1426
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1427
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1428
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1429
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1430
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1431
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1432
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1433
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1434
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1435
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1436
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1437
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1441
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1442
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1443
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1444
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1445
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1446
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1447
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1449
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1451
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1452
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1457
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1460
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1461
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1464
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1466
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1467
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1468
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1469
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1471
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1472
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1475
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1479
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1481
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1482
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1492
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1495
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1497
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1498
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1499
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1500
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1501
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1502
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1503
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1504
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1505
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1506
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1507
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1508
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1509
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1510
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1511
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1512
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1513
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1514
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1515
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1516
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1517
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1518
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1519
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1520
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1521
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1522
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1523
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1524
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1525
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1526
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1527
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1528
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1529
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1530
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1531
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1532
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1533
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1534
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1535
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1536
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1537
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1538
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1539
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1540
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1541
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1542
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1543
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1544
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1545
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1546
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1547
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1548
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1549
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1550
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1551
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1552
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1553
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1554
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1555
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1556
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1557
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1558
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1559
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1560
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1561
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1562
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1563
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1564
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1565
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1566
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1567
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1568
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1569
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1570
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1571
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1572
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1573
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1574
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1575
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1576
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1577
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1578
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1579
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1580
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1581
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1582
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1583
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1584
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1585
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1586
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1587
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1588
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1589
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1590
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1591
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1592
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1593
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1594
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1595
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1596
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1597
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1598
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1599
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1600
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1601
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1602
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1603
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1604
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1605
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1606
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1607
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1608
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1609
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1610
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1611
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1612
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1613
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1614
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1615
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1616
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1617
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1618
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1619
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1620
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1621
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1622
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1623
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1624
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1625
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1626
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1627
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1628
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1629
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1630
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1631
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1632
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1633
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1634
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1635
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1636
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1637
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1638
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1639
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1640
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1641
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1642
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1643
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1644
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1645
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1646
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1647
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1648
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1649
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1650
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1651
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1652
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1653
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1654
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1655
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1656
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1657
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1658
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1659
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1660
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1661
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1662
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1663
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1664
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1665
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1666
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1667
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1668
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1669
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1670
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1671
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1672
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1673
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1674
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1675
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1676
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1677
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1678
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1679
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1680
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1681
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1682
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1683
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1684
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1685
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1686
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1687
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1688
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1689
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1690
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1691
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1692
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1693
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1694
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1695
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1696
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1697
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1698
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1699
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1700
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1701
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1702
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1703
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1704
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1705
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1706
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1707
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1708
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1709
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1710
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1711
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1712
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1713
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1714
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1715
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1716
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1717
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1718
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1719
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1720
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1721
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1722
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1723
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1724
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1725
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1726
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1727
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1728
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1729
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1730
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1731
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1732
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1733
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1734
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1735
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1736
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1737
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1738
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1739
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1740
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1741
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1742
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1743
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1744
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1745
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1746
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1747
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
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1757
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1758
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1759
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1760
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1761
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1762
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1763
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1764
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1765
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1766
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1767
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1768
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1769
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1770
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1771
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1772
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1773
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1774
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1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
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1788
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1789
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1790
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1791
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1792
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1793
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1794
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1795
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1796
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1797
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1798
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1799
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1800
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1801
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1802
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1803
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1804
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1805
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1806
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1807
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1808
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1809
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1810
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1811
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1812
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1813
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1814
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1815
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1816
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1817
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1818
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1819
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1820
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1821
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1822
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1823
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1824
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1825
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1826
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1827
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1828
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1829
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1830
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1831
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1832
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1833
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1834
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1835
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1836
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1837
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1838
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1839
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1840
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1841
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1842
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1843
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1844
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1845
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1846
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1847
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1848
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1849
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1850
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1851
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1852
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1853
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1854
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1855
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1856
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1857
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1858
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1859
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1860
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1861
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1862
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1863
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1864
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1865
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1866
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1867
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1868
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1869
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1870
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1871
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1872
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1873
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1874
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1875
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1876
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1877
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1878
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1879
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1880
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1881
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1882
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1883
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1884
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1885
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1886
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1887
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1888
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1889
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1890
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1891
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1892
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1893
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1894
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1895
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1896
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1897
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1898
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1899
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1900
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1901
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1902
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1903
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1904
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1905
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1906
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1907
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1908
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1909
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1910
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1911
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1912
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1913
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1914
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1915
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1916
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1917
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1918
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1919
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1920
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1921
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1922
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1923
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1924
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1925
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1926
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1927
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1928
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1929
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1930
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1931
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1932
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1933
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1934
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1935
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1936
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1937
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1938
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1939
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1940
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1941
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1942
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1943
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1944
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1945
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1946
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1947
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1948
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1949
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1950
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1951
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1952
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1953
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1954
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1955
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1956
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1957
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1958
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1959
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1960
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1961
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1962
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1963
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1964
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1965
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1966
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1967
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1968
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1969
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1970
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1971
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1972
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1973
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1974
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1975
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1976
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1977
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1978
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1979
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1980
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1981
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1982
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1983
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1984
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1985
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1986
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1987
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1988
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1989
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1990
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1991
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1992
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1993
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1994
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1995
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1996
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1997
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1998
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1999
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2007
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2008
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2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
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2018
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2019
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2020
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2021
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2022
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2023
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2024
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2025
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2026
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2027
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2028
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2029
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2030
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2031
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2032
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2033
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2034
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2035
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2036
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2037
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2038
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2039
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2040
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2041
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2042
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2043
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2044
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2045
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2046
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2047
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2048
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2049
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2050
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2051
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2052
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2053
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2054
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2055
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2056
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2057
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2058
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2059
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2060
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2061
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2062
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2063
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2064
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2065
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2066
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2067
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2068
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2069
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2070
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2071
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2072
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2073
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2074
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2075
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2076
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2077
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2078
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2079
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2080
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2081
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2082
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2083
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2084
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2085
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2086
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2087
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2088
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2089
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2090
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2091
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2092
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2093
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2094
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2095
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2096
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2097
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2098
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2099
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2100
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2101
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2102
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2103
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2104
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2105
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2106
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2107
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2108
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2109
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2110
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2111
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2112
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2113
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2114
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2115
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2116
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2117
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2118
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2119
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2120
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2121
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2122
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2123
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2124
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2125
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2126
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2127
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2128
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2129
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2130
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2131
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2132
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2133
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2134
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2135
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2136
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2137
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2138
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2139
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2140
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2141
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2142
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2143
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2144
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2145
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2146
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2147
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2148
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2149
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2150
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2151
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2152
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2153
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2154
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2155
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2156
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2157
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2158
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2159
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2160
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2161
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2162
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2163
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2164
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2165
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2166
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2167
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2168
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2169
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2170
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2171
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2172
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2173
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2174
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2175
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2176
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2177
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2178
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2179
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2180
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2181
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2182
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2183
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2184
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2185
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2186
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2187
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2188
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2189
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2190
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2191
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2192
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2193
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2194
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2195
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2196
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2197
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2198
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2199
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2200
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2201
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2202
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2203
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2204
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2205
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2206
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2207
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2208
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2209
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2210
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2211
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2212
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2213
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2214
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2215
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2216
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2217
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2218
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2219
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2220
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2221
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2222
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2223
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2224
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2225
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2226
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2227
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2228
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2229
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2230
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2231
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2232
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2233
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2234
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2235
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2236
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2237
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2238
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2239
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2240
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2241
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2242
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2243
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2244
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2245
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2246
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2247
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2248
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2249
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2250
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2251
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2252
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2253
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2254
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2255
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2256
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2257
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2258
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2259
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2260
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2261
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2262
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2263
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2264
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2265
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2266
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2267
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2268
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2269
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2270
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2271
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2272
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2273
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2274
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2275
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2276
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2277
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2278
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2279
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2280
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2281
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2282
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2283
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2284
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2285
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2286
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2287
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2288
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2289
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2290
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2291
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2292
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2293
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2294
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2295
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2296
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2297
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2298
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2299
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2300
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2301
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2302
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2303
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2304
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2305
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2306
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2307
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2308
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2309
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2310
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2311
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2312
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2313
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2314
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2315
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2316
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2317
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2318
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2319
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2320
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2321
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2322
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2323
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2324
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2325
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2326
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2327
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2328
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2329
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2330
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2331
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2332
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2333
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2334
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2335
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2336
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2337
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2338
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2339
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2340
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2341
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2342
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2343
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2344
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2345
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2346
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2347
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2348
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2349
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2350
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2351
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2352
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2353
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2354
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2355
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2356
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2357
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2358
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2359
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2360
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2361
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2362
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2363
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2364
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2365
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2366
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2367
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2368
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2369
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2370
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2371
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2372
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2373
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2374
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2375
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2376
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2377
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2378
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2379
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2380
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2381
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2382
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2383
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2384
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2385
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2386
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2387
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2388
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2389
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2390
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2391
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2392
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2393
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2394
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2395
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2396
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2397
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2398
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2399
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2400
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2401
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2402
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2403
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2404
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2405
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2406
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2407
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2408
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2409
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2410
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2411
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2412
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2413
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2414
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2415
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2416
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2417
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2418
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2419
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2420
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2421
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2422
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2423
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2424
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2425
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2426
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2427
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2428
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2429
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2430
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2431
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2432
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2433
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2434
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2435
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2436
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2437
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2438
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2439
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2440
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2441
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2442
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2443
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2444
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2445
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2446
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2447
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2448
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2449
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2450
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2451
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2452
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2453
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2454
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2455
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2456
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2457
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2458
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2459
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2460
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2461
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2462
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2463
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2464
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2465
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2466
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2467
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2468
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2469
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2470
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2471
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2472
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2473
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2474
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2475
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2476
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2477
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2478
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2479
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2480
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2481
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2482
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2483
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2484
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2485
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2486
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2487
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2488
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2489
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2490
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2491
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2492
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2493
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2494
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2495
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2496
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2497
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2498
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2499
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2500
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2501
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2502
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2503
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2504
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2505
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2506
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2507
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2508
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2509
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2510
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2511
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2512
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2513
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2514
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2515
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2516
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2517
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2518
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2519
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2520
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2521
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2522
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2523
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2524
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2525
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2526
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2527
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2528
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2529
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2530
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2531
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2532
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2533
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2534
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2535
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2536
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2537
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2538
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2539
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2540
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2541
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2542
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2543
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2544
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2545
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2546
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2547
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2548
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2549
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2550
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2551
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2552
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2553
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2554
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2555
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2556
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2557
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2558
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2559
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2560
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2561
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2562
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2563
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2564
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2565
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2566
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2567
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2568
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2569
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2570
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2571
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2572
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2573
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2574
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2575
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2576
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2577
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2578
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2579
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2580
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2581
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2582
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2583
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2584
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2585
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2586
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2587
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2588
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2589
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2590
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2591
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2592
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2593
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2594
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2595
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2596
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3112
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3141
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3243
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3260
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3261
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3262
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3264
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3265
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3267
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3268
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3269
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3270
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3271
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3272
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3273
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3274
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3275
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3276
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3277
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3278
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3279
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3280
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3281
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3291
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3292
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3293
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3294
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3295
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3792
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3800
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3810
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3811
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3812
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3821
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3827
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3828
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3829
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