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scenario-kd-scr-ner-full-mdeberta_data-univner_full55

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  1. README.md +42 -42
  2. eval_result_ner.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,14 +1,14 @@
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  ---
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- base_model: haryoaw/scenario-TCR-NER_data-univner_full
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  library_name: transformers
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  license: mit
 
 
 
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  metrics:
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  - precision
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  - recall
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  - f1
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  - accuracy
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- tags:
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- - generated_from_trainer
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  model-index:
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  - name: scenario-kd-scr-ner-full-mdeberta_data-univner_full55
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  results: []
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_full](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_full) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 180.1557
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- - Precision: 0.6958
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- - Recall: 0.6184
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- - F1: 0.6548
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- - Accuracy: 0.9663
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  ## Model description
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@@ -58,40 +58,40 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 626.3253 | 0.2911 | 500 | 559.5172 | 0.0 | 0.0 | 0.0 | 0.9241 |
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- | 529.6569 | 0.5822 | 1000 | 503.3665 | 0.3596 | 0.0105 | 0.0205 | 0.9244 |
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- | 481.9473 | 0.8732 | 1500 | 463.3378 | 0.2837 | 0.1236 | 0.1722 | 0.9308 |
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- | 444.8498 | 1.1643 | 2000 | 433.5602 | 0.4233 | 0.0649 | 0.1126 | 0.9292 |
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- | 415.1952 | 1.4554 | 2500 | 405.7039 | 0.4916 | 0.3197 | 0.3874 | 0.9445 |
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- | 391.3191 | 1.7465 | 3000 | 383.5480 | 0.5120 | 0.4115 | 0.4563 | 0.9502 |
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- | 369.4905 | 2.0375 | 3500 | 365.8290 | 0.6227 | 0.3294 | 0.4309 | 0.9480 |
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- | 349.644 | 2.3286 | 4000 | 346.1183 | 0.5629 | 0.4978 | 0.5283 | 0.9559 |
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- | 332.7872 | 2.6197 | 4500 | 330.6745 | 0.6230 | 0.4712 | 0.5366 | 0.9572 |
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- | 317.7756 | 2.9108 | 5000 | 316.2125 | 0.6176 | 0.4956 | 0.5499 | 0.9578 |
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- | 302.8933 | 3.2019 | 5500 | 303.1108 | 0.5772 | 0.5927 | 0.5849 | 0.9589 |
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- | 289.8367 | 3.4929 | 6000 | 290.9793 | 0.6669 | 0.5076 | 0.5764 | 0.9592 |
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- | 278.486 | 3.7840 | 6500 | 280.2549 | 0.6664 | 0.5281 | 0.5892 | 0.9609 |
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- | 267.5123 | 4.0751 | 7000 | 268.7850 | 0.6370 | 0.5949 | 0.6152 | 0.9624 |
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- | 256.5175 | 4.3662 | 7500 | 259.0105 | 0.6526 | 0.5790 | 0.6136 | 0.9631 |
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- | 247.65 | 4.6573 | 8000 | 250.2907 | 0.6609 | 0.6012 | 0.6296 | 0.9641 |
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- | 239.1523 | 4.9483 | 8500 | 242.1396 | 0.6456 | 0.6044 | 0.6243 | 0.9635 |
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- | 230.5722 | 5.2394 | 9000 | 234.5265 | 0.6762 | 0.5849 | 0.6273 | 0.9641 |
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- | 222.7519 | 5.5305 | 9500 | 227.1519 | 0.6838 | 0.5923 | 0.6348 | 0.9645 |
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- | 216.3841 | 5.8216 | 10000 | 221.0167 | 0.6938 | 0.5787 | 0.6311 | 0.9643 |
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- | 210.8608 | 6.1126 | 10500 | 215.2167 | 0.6795 | 0.5965 | 0.6353 | 0.9642 |
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- | 204.422 | 6.4037 | 11000 | 209.7950 | 0.6663 | 0.6214 | 0.6431 | 0.9654 |
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- | 199.5391 | 6.6948 | 11500 | 205.1505 | 0.6723 | 0.6110 | 0.6402 | 0.9650 |
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- | 194.9082 | 6.9859 | 12000 | 200.7199 | 0.6870 | 0.6113 | 0.6470 | 0.9650 |
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- | 190.3632 | 7.2770 | 12500 | 197.2017 | 0.6975 | 0.6035 | 0.6471 | 0.9651 |
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- | 186.9785 | 7.5680 | 13000 | 193.4576 | 0.6772 | 0.6265 | 0.6508 | 0.9655 |
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- | 183.9405 | 7.8591 | 13500 | 190.7187 | 0.6875 | 0.6126 | 0.6479 | 0.9656 |
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- | 181.0169 | 8.1502 | 14000 | 187.9661 | 0.6840 | 0.6324 | 0.6572 | 0.9663 |
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- | 178.3527 | 8.4413 | 14500 | 185.6701 | 0.7029 | 0.6076 | 0.6518 | 0.9657 |
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- | 176.2939 | 8.7324 | 15000 | 183.7507 | 0.6892 | 0.6102 | 0.6473 | 0.9660 |
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- | 174.6214 | 9.0234 | 15500 | 182.2909 | 0.6843 | 0.6259 | 0.6538 | 0.9664 |
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- | 173.2938 | 9.3145 | 16000 | 181.6205 | 0.6963 | 0.5976 | 0.6432 | 0.9649 |
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- | 172.1101 | 9.6056 | 16500 | 180.5871 | 0.6886 | 0.6272 | 0.6564 | 0.9664 |
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- | 172.1252 | 9.8967 | 17000 | 180.1557 | 0.6958 | 0.6184 | 0.6548 | 0.9663 |
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  ### Framework versions
 
1
  ---
 
2
  library_name: transformers
3
  license: mit
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+ base_model: haryoaw/scenario-TCR-NER_data-univner_full
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+ tags:
6
+ - generated_from_trainer
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  metrics:
8
  - precision
9
  - recall
10
  - f1
11
  - accuracy
 
 
12
  model-index:
13
  - name: scenario-kd-scr-ner-full-mdeberta_data-univner_full55
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  results: []
 
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  This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_full](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_full) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 182.5497
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+ - Precision: 0.6804
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+ - Recall: 0.6154
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+ - F1: 0.6463
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+ - Accuracy: 0.9657
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  ## Model description
31
 
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 627.6279 | 0.2911 | 500 | 560.3030 | 0.0 | 0.0 | 0.0 | 0.9241 |
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+ | 529.0723 | 0.5822 | 1000 | 503.1468 | 0.3145 | 0.0378 | 0.0675 | 0.9253 |
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+ | 481.2237 | 0.8732 | 1500 | 462.0725 | 0.3110 | 0.0811 | 0.1286 | 0.9284 |
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+ | 443.6023 | 1.1643 | 2000 | 431.7476 | 0.4241 | 0.0822 | 0.1378 | 0.9304 |
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+ | 413.7332 | 1.4554 | 2500 | 404.1758 | 0.4897 | 0.3199 | 0.3870 | 0.9448 |
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+ | 389.6206 | 1.7465 | 3000 | 381.5862 | 0.5329 | 0.3800 | 0.4437 | 0.9494 |
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+ | 368.3142 | 2.0375 | 3500 | 363.5359 | 0.5888 | 0.3769 | 0.4596 | 0.9507 |
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+ | 349.4665 | 2.3286 | 4000 | 346.6397 | 0.5410 | 0.4793 | 0.5083 | 0.9539 |
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+ | 333.3893 | 2.6197 | 4500 | 331.5422 | 0.6223 | 0.4291 | 0.5079 | 0.9550 |
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+ | 318.8641 | 2.9108 | 5000 | 316.8669 | 0.5984 | 0.5612 | 0.5792 | 0.9597 |
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+ | 303.8825 | 3.2019 | 5500 | 303.3675 | 0.6190 | 0.5569 | 0.5863 | 0.9608 |
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+ | 290.8802 | 3.4929 | 6000 | 291.3924 | 0.6347 | 0.5390 | 0.5830 | 0.9606 |
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+ | 279.9562 | 3.7840 | 6500 | 281.3740 | 0.6484 | 0.5403 | 0.5894 | 0.9613 |
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+ | 268.853 | 4.0751 | 7000 | 270.4638 | 0.6513 | 0.5578 | 0.6009 | 0.9615 |
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+ | 257.9733 | 4.3662 | 7500 | 260.5476 | 0.6536 | 0.5817 | 0.6156 | 0.9635 |
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+ | 248.9305 | 4.6573 | 8000 | 251.8452 | 0.6631 | 0.5926 | 0.6258 | 0.9638 |
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+ | 240.7242 | 4.9483 | 8500 | 243.8925 | 0.6587 | 0.5882 | 0.6215 | 0.9633 |
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+ | 232.3709 | 5.2394 | 9000 | 236.3189 | 0.6514 | 0.6077 | 0.6288 | 0.9640 |
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+ | 224.6698 | 5.5305 | 9500 | 229.3991 | 0.6675 | 0.5722 | 0.6162 | 0.9629 |
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+ | 218.3664 | 5.8216 | 10000 | 223.3077 | 0.6788 | 0.5823 | 0.6269 | 0.9639 |
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+ | 212.9249 | 6.1126 | 10500 | 217.2704 | 0.6717 | 0.6003 | 0.6340 | 0.9643 |
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+ | 206.6058 | 6.4037 | 11000 | 211.8754 | 0.6570 | 0.6226 | 0.6393 | 0.9649 |
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+ | 201.722 | 6.6948 | 11500 | 207.1151 | 0.6680 | 0.6210 | 0.6436 | 0.9650 |
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+ | 197.034 | 6.9859 | 12000 | 202.9470 | 0.6805 | 0.6047 | 0.6403 | 0.9649 |
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+ | 192.5555 | 7.2770 | 12500 | 199.1373 | 0.6749 | 0.6130 | 0.6425 | 0.9651 |
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+ | 189.1607 | 7.5680 | 13000 | 195.9332 | 0.6605 | 0.6279 | 0.6438 | 0.9652 |
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+ | 186.1884 | 7.8591 | 13500 | 193.1577 | 0.6772 | 0.6057 | 0.6395 | 0.9652 |
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+ | 183.2947 | 8.1502 | 14000 | 190.2176 | 0.6697 | 0.6318 | 0.6502 | 0.9654 |
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+ | 180.5764 | 8.4413 | 14500 | 187.9859 | 0.6970 | 0.6091 | 0.6501 | 0.9657 |
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+ | 178.5341 | 8.7324 | 15000 | 186.4189 | 0.6843 | 0.5976 | 0.6380 | 0.9645 |
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+ | 176.79 | 9.0234 | 15500 | 184.5720 | 0.6846 | 0.6198 | 0.6506 | 0.9661 |
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+ | 175.528 | 9.3145 | 16000 | 183.8221 | 0.7059 | 0.5905 | 0.6431 | 0.9650 |
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+ | 174.3179 | 9.6056 | 16500 | 182.7365 | 0.6842 | 0.6188 | 0.6498 | 0.9658 |
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+ | 174.2736 | 9.8967 | 17000 | 182.5497 | 0.6804 | 0.6154 | 0.6463 | 0.9657 |
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  ### Framework versions
eval_result_ner.json CHANGED
@@ -1 +1 @@
1
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