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final_V2-bert-after-adding-new-words-text-classification-model

Text Classification
Transformers
Safetensors
bert
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AmirlyPhd/final_V2-bert-after-adding-new-words-text-classification-model

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Files changed (9) hide show
  1. README.md +92 -0
  2. added_tokens.json +121 -0
  3. config.json +45 -0
  4. model.safetensors +3 -0
  5. special_tokens_map.json +37 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +1121 -0
  8. training_args.bin +3 -0
  9. 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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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: final_V2-bert-after-adding-new-words-text-classification-model
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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_V2-bert-after-adding-new-words-text-classification-model
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+
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+ This model was trained from scratch on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1494
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+ - Accuracy: 0.9716
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+ - F1: 0.8348
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+ - Precision: 0.8317
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+ - Recall: 0.8385
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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: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 32
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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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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 3
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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 | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.8136 | 0.11 | 50 | 1.7501 | 0.3470 | 0.1733 | 0.3034 | 0.1944 |
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+ | 0.9023 | 0.22 | 100 | 1.2121 | 0.5723 | 0.3083 | 0.3496 | 0.3189 |
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+ | 0.5924 | 0.33 | 150 | 0.9662 | 0.6667 | 0.3919 | 0.4265 | 0.4037 |
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+ | 0.4218 | 0.44 | 200 | 0.4848 | 0.8813 | 0.6427 | 0.6492 | 0.6413 |
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+ | 0.2025 | 0.55 | 250 | 0.3807 | 0.9021 | 0.6677 | 0.6538 | 0.6829 |
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+ | 0.1609 | 0.66 | 300 | 0.3360 | 0.9147 | 0.6763 | 0.6727 | 0.6822 |
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+ | 0.2035 | 0.76 | 350 | 0.3705 | 0.8991 | 0.6711 | 0.6589 | 0.6838 |
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+ | 0.1208 | 0.87 | 400 | 0.2140 | 0.9565 | 0.8218 | 0.8137 | 0.8323 |
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+ | 0.1313 | 0.98 | 450 | 0.6818 | 0.8704 | 0.6779 | 0.7179 | 0.6859 |
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+ | 0.1576 | 1.09 | 500 | 0.2508 | 0.9212 | 0.7443 | 0.7888 | 0.7311 |
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+ | 0.0593 | 1.2 | 550 | 0.2091 | 0.9552 | 0.8193 | 0.8179 | 0.8227 |
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+ | 0.0705 | 1.31 | 600 | 0.2010 | 0.9552 | 0.8154 | 0.8091 | 0.8225 |
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+ | 0.0637 | 1.42 | 650 | 0.1985 | 0.9573 | 0.8187 | 0.8115 | 0.8275 |
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+ | 0.0619 | 1.53 | 700 | 0.2306 | 0.9541 | 0.8241 | 0.8194 | 0.8301 |
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+ | 0.0582 | 1.64 | 750 | 0.2001 | 0.9609 | 0.8280 | 0.8250 | 0.8320 |
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+ | 0.1132 | 1.75 | 800 | 0.1439 | 0.9680 | 0.8324 | 0.8284 | 0.8367 |
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+ | 0.0416 | 1.86 | 850 | 0.1558 | 0.9680 | 0.8333 | 0.8301 | 0.8369 |
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+ | 0.0371 | 1.97 | 900 | 0.2242 | 0.9595 | 0.8280 | 0.8235 | 0.8345 |
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+ | 0.0428 | 2.07 | 950 | 0.1907 | 0.9617 | 0.8303 | 0.8262 | 0.8356 |
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+ | 0.0388 | 2.18 | 1000 | 0.1784 | 0.9658 | 0.8319 | 0.8266 | 0.8383 |
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+ | 0.0335 | 2.29 | 1050 | 0.1735 | 0.9675 | 0.8323 | 0.8266 | 0.8390 |
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+ | 0.0361 | 2.4 | 1100 | 0.1921 | 0.9636 | 0.8283 | 0.8219 | 0.8360 |
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+ | 0.0126 | 2.51 | 1150 | 0.2200 | 0.9614 | 0.8294 | 0.8274 | 0.8327 |
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+ | 0.003 | 2.62 | 1200 | 0.2251 | 0.9614 | 0.8296 | 0.8262 | 0.8346 |
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+ | 0.0029 | 2.73 | 1250 | 0.1750 | 0.9694 | 0.8348 | 0.8314 | 0.8388 |
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+ | 0.0137 | 2.84 | 1300 | 0.1775 | 0.9686 | 0.8345 | 0.8300 | 0.8397 |
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+ | 0.0184 | 2.95 | 1350 | 0.1860 | 0.9675 | 0.8337 | 0.8293 | 0.8391 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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148
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151
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152
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156
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159
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160
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163
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164
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172
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180
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183
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184
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185
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188
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192
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193
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195
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196
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199
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201
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204
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207
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212
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215
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216
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217
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220
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224
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228
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233
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236
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244
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249
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252
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255
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257
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260
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263
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264
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271
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272
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273
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276
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279
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280
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281
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284
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287
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288
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289
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292
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296
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297
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300
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311
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312
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313
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316
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319
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320
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321
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324
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328
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329
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332
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340
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440
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480
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624
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729
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740
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761
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764
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768
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769
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772
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776
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777
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780
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781
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785
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790
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791
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792
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793
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796
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799
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800
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801
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804
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807
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808
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812
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816
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825
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832
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833
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840
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852
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