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scenario-kd-scr-ner-full-xlmr_data-univner_full44

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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-xlmr_data-univner_full44
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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: 159.5619
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- - Precision: 0.5629
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- - Recall: 0.5487
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- - F1: 0.5557
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- - Accuracy: 0.9595
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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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- | 464.3983 | 0.2911 | 500 | 386.3483 | 0.0 | 0.0 | 0.0 | 0.9241 |
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- | 363.3697 | 0.5822 | 1000 | 346.0058 | 0.3862 | 0.0362 | 0.0662 | 0.9257 |
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- | 332.4401 | 0.8732 | 1500 | 323.5819 | 0.3717 | 0.0821 | 0.1345 | 0.9275 |
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- | 310.8773 | 1.1643 | 2000 | 304.6088 | 0.2963 | 0.1405 | 0.1906 | 0.9307 |
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- | 293.7644 | 1.4554 | 2500 | 289.6203 | 0.3156 | 0.1463 | 0.1999 | 0.9316 |
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- | 278.9045 | 1.7465 | 3000 | 275.8072 | 0.4021 | 0.1476 | 0.2159 | 0.9335 |
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- | 264.6502 | 2.0375 | 3500 | 262.6655 | 0.3527 | 0.2535 | 0.2950 | 0.9395 |
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- | 251.8785 | 2.3286 | 4000 | 252.7831 | 0.4299 | 0.2371 | 0.3056 | 0.9401 |
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- | 242.5807 | 2.6197 | 4500 | 242.9949 | 0.3826 | 0.3297 | 0.3542 | 0.9424 |
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- | 232.9433 | 2.9108 | 5000 | 235.2073 | 0.4179 | 0.2731 | 0.3303 | 0.9426 |
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- | 224.0413 | 3.2019 | 5500 | 226.1858 | 0.4338 | 0.3601 | 0.3935 | 0.9476 |
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- | 215.9923 | 3.4929 | 6000 | 219.0613 | 0.4422 | 0.4040 | 0.4222 | 0.9505 |
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- | 208.5193 | 3.7840 | 6500 | 212.5694 | 0.4516 | 0.4474 | 0.4495 | 0.9524 |
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- | 202.1674 | 4.0751 | 7000 | 206.1281 | 0.4977 | 0.4540 | 0.4749 | 0.9540 |
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- | 195.8605 | 4.3662 | 7500 | 201.2849 | 0.5100 | 0.4546 | 0.4807 | 0.9545 |
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- | 190.8603 | 4.6573 | 8000 | 196.3180 | 0.5162 | 0.4711 | 0.4926 | 0.9550 |
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- | 186.0957 | 4.9483 | 8500 | 191.7499 | 0.4873 | 0.4963 | 0.4917 | 0.9552 |
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- | 180.8985 | 5.2394 | 9000 | 187.6076 | 0.5037 | 0.5155 | 0.5095 | 0.9561 |
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- | 176.8238 | 5.5305 | 9500 | 184.3026 | 0.5073 | 0.5279 | 0.5174 | 0.9556 |
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- | 174.0782 | 5.8216 | 10000 | 180.7152 | 0.5563 | 0.4965 | 0.5247 | 0.9572 |
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- | 170.4269 | 6.1126 | 10500 | 178.1061 | 0.5247 | 0.4783 | 0.5004 | 0.9558 |
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- | 167.3528 | 6.4037 | 11000 | 175.0525 | 0.5511 | 0.5145 | 0.5322 | 0.9578 |
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- | 164.7345 | 6.6948 | 11500 | 172.4756 | 0.5393 | 0.5096 | 0.5240 | 0.9577 |
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- | 162.046 | 6.9859 | 12000 | 170.3612 | 0.5405 | 0.5409 | 0.5407 | 0.9587 |
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- | 159.77 | 7.2770 | 12500 | 168.4884 | 0.5557 | 0.5136 | 0.5339 | 0.9583 |
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- | 157.6139 | 7.5680 | 13000 | 166.3754 | 0.5508 | 0.5197 | 0.5348 | 0.9586 |
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- | 156.2242 | 7.8591 | 13500 | 164.9902 | 0.5545 | 0.5347 | 0.5444 | 0.9594 |
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- | 154.4512 | 8.1502 | 14000 | 163.5688 | 0.5592 | 0.5503 | 0.5547 | 0.9596 |
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- | 153.0177 | 8.4413 | 14500 | 162.4043 | 0.5450 | 0.5631 | 0.5539 | 0.9592 |
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- | 152.2476 | 8.7324 | 15000 | 161.5181 | 0.5624 | 0.5496 | 0.5559 | 0.9591 |
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- | 151.1821 | 9.0234 | 15500 | 160.7868 | 0.5558 | 0.5484 | 0.5521 | 0.9593 |
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- | 150.0763 | 9.3145 | 16000 | 160.2223 | 0.5622 | 0.5364 | 0.5490 | 0.9594 |
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- | 149.6415 | 9.6056 | 16500 | 159.8312 | 0.5697 | 0.5374 | 0.5531 | 0.9598 |
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- | 149.7359 | 9.8967 | 17000 | 159.5619 | 0.5629 | 0.5487 | 0.5557 | 0.9595 |
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  ### Framework versions
 
1
  ---
 
2
  library_name: transformers
3
  license: mit
4
+ 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-xlmr_data-univner_full44
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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: 158.9407
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+ - Precision: 0.5487
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+ - Recall: 0.5432
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+ - F1: 0.5459
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+ - Accuracy: 0.9588
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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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+ | 460.9453 | 0.2911 | 500 | 385.8351 | 0.0 | 0.0 | 0.0 | 0.9241 |
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+ | 363.4557 | 0.5822 | 1000 | 346.2052 | 0.4279 | 0.0544 | 0.0965 | 0.9263 |
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+ | 332.2012 | 0.8732 | 1500 | 325.9525 | 0.3466 | 0.0752 | 0.1235 | 0.9270 |
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+ | 311.0392 | 1.1643 | 2000 | 305.0690 | 0.2719 | 0.1538 | 0.1965 | 0.9302 |
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+ | 293.6181 | 1.4554 | 2500 | 289.0764 | 0.2902 | 0.1616 | 0.2076 | 0.9319 |
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+ | 278.0759 | 1.7465 | 3000 | 274.3208 | 0.3437 | 0.1727 | 0.2299 | 0.9351 |
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+ | 263.7235 | 2.0375 | 3500 | 261.5710 | 0.3720 | 0.2477 | 0.2974 | 0.9395 |
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+ | 250.8804 | 2.3286 | 4000 | 251.6802 | 0.4335 | 0.2371 | 0.3065 | 0.9399 |
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+ | 241.6486 | 2.6197 | 4500 | 241.4983 | 0.3763 | 0.3122 | 0.3413 | 0.9431 |
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+ | 232.1585 | 2.9108 | 5000 | 234.7022 | 0.4332 | 0.2502 | 0.3172 | 0.9419 |
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+ | 223.428 | 3.2019 | 5500 | 225.8982 | 0.4283 | 0.3369 | 0.3771 | 0.9458 |
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+ | 215.7432 | 3.4929 | 6000 | 218.6250 | 0.4172 | 0.3455 | 0.3780 | 0.9469 |
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+ | 208.5821 | 3.7840 | 6500 | 212.5754 | 0.4244 | 0.4311 | 0.4277 | 0.9480 |
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+ | 202.7347 | 4.0751 | 7000 | 206.2203 | 0.4440 | 0.4046 | 0.4233 | 0.9502 |
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+ | 196.2593 | 4.3662 | 7500 | 200.8361 | 0.4877 | 0.4275 | 0.4556 | 0.9518 |
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+ | 191.1748 | 4.6573 | 8000 | 196.1823 | 0.4735 | 0.4281 | 0.4496 | 0.9524 |
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+ | 186.3328 | 4.9483 | 8500 | 191.5347 | 0.4679 | 0.4555 | 0.4616 | 0.9531 |
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+ | 180.9869 | 5.2394 | 9000 | 187.5859 | 0.4850 | 0.4979 | 0.4914 | 0.9549 |
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+ | 176.8171 | 5.5305 | 9500 | 183.7527 | 0.4858 | 0.5217 | 0.5031 | 0.9551 |
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+ | 173.9635 | 5.8216 | 10000 | 180.3877 | 0.5310 | 0.4719 | 0.4997 | 0.9553 |
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+ | 170.1918 | 6.1126 | 10500 | 177.5785 | 0.5234 | 0.4582 | 0.4887 | 0.9556 |
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+ | 167.0458 | 6.4037 | 11000 | 174.8427 | 0.5411 | 0.4620 | 0.4984 | 0.9554 |
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+ | 164.3432 | 6.6948 | 11500 | 171.9410 | 0.5348 | 0.5089 | 0.5215 | 0.9570 |
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+ | 161.6384 | 6.9859 | 12000 | 169.9951 | 0.5304 | 0.5017 | 0.5156 | 0.9573 |
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+ | 159.3906 | 7.2770 | 12500 | 167.7097 | 0.5450 | 0.5037 | 0.5235 | 0.9576 |
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+ | 157.2167 | 7.5680 | 13000 | 165.9562 | 0.5248 | 0.5260 | 0.5254 | 0.9578 |
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+ | 155.8673 | 7.8591 | 13500 | 164.2853 | 0.5485 | 0.5210 | 0.5344 | 0.9581 |
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+ | 153.9819 | 8.1502 | 14000 | 162.9678 | 0.5385 | 0.5161 | 0.5271 | 0.9581 |
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+ | 152.5708 | 8.4413 | 14500 | 161.7499 | 0.5424 | 0.5385 | 0.5404 | 0.9583 |
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+ | 151.7945 | 8.7324 | 15000 | 160.7884 | 0.5528 | 0.5282 | 0.5402 | 0.9585 |
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+ | 150.7972 | 9.0234 | 15500 | 160.0030 | 0.5441 | 0.5455 | 0.5448 | 0.9590 |
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+ | 149.6132 | 9.3145 | 16000 | 159.5214 | 0.5446 | 0.5474 | 0.5460 | 0.9585 |
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+ | 149.1168 | 9.6056 | 16500 | 159.1108 | 0.5540 | 0.5376 | 0.5457 | 0.9588 |
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+ | 149.234 | 9.8967 | 17000 | 158.9407 | 0.5487 | 0.5432 | 0.5459 | 0.9588 |
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  ### Framework versions
eval_result_ner.json CHANGED
@@ -1 +1 @@
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