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scenario-kd-scr-ner-half-xlmr_data-univner_full66

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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-half-xlmr_data-univner_full66
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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: 120.2460
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- - Precision: 0.4418
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- - Recall: 0.4111
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- - F1: 0.4259
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- - Accuracy: 0.9508
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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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- | 257.7836 | 0.2911 | 500 | 190.0373 | 0.0 | 0.0 | 0.0 | 0.9241 |
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- | 179.3866 | 0.5822 | 1000 | 173.8501 | 0.4324 | 0.0023 | 0.0046 | 0.9242 |
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- | 167.4276 | 0.8732 | 1500 | 164.6176 | 0.4172 | 0.0196 | 0.0375 | 0.9249 |
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- | 160.874 | 1.1643 | 2000 | 160.7553 | 0.4603 | 0.0042 | 0.0083 | 0.9243 |
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- | 155.3677 | 1.4554 | 2500 | 154.5823 | 0.2516 | 0.0685 | 0.1077 | 0.9268 |
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- | 151.6743 | 1.7465 | 3000 | 151.6693 | 0.3540 | 0.0594 | 0.1018 | 0.9267 |
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- | 147.7351 | 2.0375 | 3500 | 147.3540 | 0.2816 | 0.0925 | 0.1392 | 0.9277 |
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- | 144.2784 | 2.3286 | 4000 | 144.3419 | 0.2836 | 0.1122 | 0.1608 | 0.9285 |
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- | 141.5455 | 2.6197 | 4500 | 141.6975 | 0.2921 | 0.1101 | 0.1599 | 0.9293 |
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- | 139.1013 | 2.9108 | 5000 | 139.2388 | 0.2906 | 0.1260 | 0.1757 | 0.9311 |
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- | 135.433 | 3.2019 | 5500 | 137.0034 | 0.2676 | 0.1945 | 0.2252 | 0.9334 |
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- | 133.6936 | 3.4929 | 6000 | 135.0955 | 0.2873 | 0.1860 | 0.2258 | 0.9350 |
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- | 131.3839 | 3.7840 | 6500 | 133.8098 | 0.2778 | 0.1666 | 0.2083 | 0.9350 |
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- | 129.797 | 4.0751 | 7000 | 132.1772 | 0.2916 | 0.1961 | 0.2345 | 0.9369 |
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- | 127.666 | 4.3662 | 7500 | 130.7785 | 0.3195 | 0.2108 | 0.2540 | 0.9380 |
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- | 126.5971 | 4.6573 | 8000 | 129.6297 | 0.3243 | 0.2394 | 0.2754 | 0.9392 |
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- | 125.6906 | 4.9483 | 8500 | 128.3762 | 0.3276 | 0.2613 | 0.2907 | 0.9403 |
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- | 124.4524 | 5.2394 | 9000 | 127.9805 | 0.3305 | 0.2536 | 0.2870 | 0.9410 |
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- | 122.7245 | 5.5305 | 9500 | 126.6189 | 0.3384 | 0.2789 | 0.3058 | 0.9418 |
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- | 121.9463 | 5.8216 | 10000 | 125.9754 | 0.3504 | 0.2995 | 0.3230 | 0.9422 |
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- | 120.7658 | 6.1126 | 10500 | 125.1251 | 0.3666 | 0.2923 | 0.3253 | 0.9438 |
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- | 119.7118 | 6.4037 | 11000 | 124.2384 | 0.3649 | 0.3300 | 0.3466 | 0.9451 |
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- | 119.2242 | 6.6948 | 11500 | 123.6015 | 0.3891 | 0.3443 | 0.3653 | 0.9456 |
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- | 118.7415 | 6.9859 | 12000 | 123.2859 | 0.4014 | 0.3474 | 0.3725 | 0.9462 |
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- | 117.3371 | 7.2770 | 12500 | 122.5413 | 0.4022 | 0.3730 | 0.3870 | 0.9480 |
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- | 116.8112 | 7.5680 | 13000 | 122.0957 | 0.4210 | 0.3542 | 0.3847 | 0.9477 |
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- | 116.6829 | 7.8591 | 13500 | 121.7368 | 0.4190 | 0.3939 | 0.4060 | 0.9491 |
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- | 116.0694 | 8.1502 | 14000 | 121.2429 | 0.4264 | 0.4098 | 0.4179 | 0.9501 |
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- | 115.1811 | 8.4413 | 14500 | 120.9883 | 0.4293 | 0.4087 | 0.4188 | 0.9497 |
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- | 115.0686 | 8.7324 | 15000 | 120.9065 | 0.4307 | 0.3806 | 0.4041 | 0.9493 |
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- | 114.9443 | 9.0234 | 15500 | 120.5293 | 0.4313 | 0.4005 | 0.4153 | 0.9499 |
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- | 114.2954 | 9.3145 | 16000 | 120.3870 | 0.4287 | 0.4160 | 0.4222 | 0.9501 |
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- | 114.2907 | 9.6056 | 16500 | 120.1462 | 0.4380 | 0.4135 | 0.4254 | 0.9511 |
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- | 114.2952 | 9.8967 | 17000 | 120.2460 | 0.4418 | 0.4111 | 0.4259 | 0.9508 |
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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:
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+ - 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-half-xlmr_data-univner_full66
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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: 121.6095
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+ - Precision: 0.4270
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+ - Recall: 0.3784
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+ - F1: 0.4013
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+ - Accuracy: 0.9476
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 259.2613 | 0.2911 | 500 | 189.6813 | 0.0 | 0.0 | 0.0 | 0.9241 |
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+ | 179.4566 | 0.5822 | 1000 | 173.2544 | 0.4545 | 0.0137 | 0.0266 | 0.9246 |
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+ | 167.777 | 0.8732 | 1500 | 164.4018 | 0.3561 | 0.0361 | 0.0655 | 0.9256 |
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+ | 160.7257 | 1.1643 | 2000 | 159.5333 | 0.0954 | 0.0042 | 0.0080 | 0.9243 |
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+ | 155.3029 | 1.4554 | 2500 | 156.0974 | 0.2908 | 0.0283 | 0.0515 | 0.9254 |
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+ | 152.3202 | 1.7465 | 3000 | 151.0953 | 0.2614 | 0.0521 | 0.0869 | 0.9266 |
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+ | 148.4375 | 2.0375 | 3500 | 149.1951 | 0.4117 | 0.0326 | 0.0604 | 0.9256 |
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+ | 144.8759 | 2.3286 | 4000 | 144.9364 | 0.2888 | 0.1091 | 0.1583 | 0.9284 |
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+ | 141.9512 | 2.6197 | 4500 | 142.7550 | 0.3105 | 0.1097 | 0.1621 | 0.9288 |
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+ | 139.8162 | 2.9108 | 5000 | 140.1311 | 0.3438 | 0.0981 | 0.1527 | 0.9289 |
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+ | 136.3472 | 3.2019 | 5500 | 138.3547 | 0.2671 | 0.1955 | 0.2258 | 0.9327 |
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+ | 134.5775 | 3.4929 | 6000 | 135.6351 | 0.2823 | 0.1747 | 0.2158 | 0.9340 |
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+ | 132.1038 | 3.7840 | 6500 | 134.0777 | 0.2685 | 0.1773 | 0.2136 | 0.9349 |
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+ | 130.6851 | 4.0751 | 7000 | 132.9280 | 0.2858 | 0.1840 | 0.2238 | 0.9359 |
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+ | 128.5001 | 4.3662 | 7500 | 131.8978 | 0.3058 | 0.2001 | 0.2419 | 0.9369 |
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+ | 127.3796 | 4.6573 | 8000 | 130.3655 | 0.3250 | 0.2151 | 0.2589 | 0.9378 |
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+ | 126.5618 | 4.9483 | 8500 | 129.1083 | 0.3273 | 0.2332 | 0.2723 | 0.9383 |
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+ | 125.2975 | 5.2394 | 9000 | 128.4492 | 0.3147 | 0.2560 | 0.2823 | 0.9396 |
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+ | 123.5341 | 5.5305 | 9500 | 127.2300 | 0.3418 | 0.2580 | 0.2940 | 0.9405 |
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+ | 122.698 | 5.8216 | 10000 | 126.8739 | 0.3390 | 0.2811 | 0.3073 | 0.9402 |
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+ | 121.6237 | 6.1126 | 10500 | 125.7438 | 0.3739 | 0.3011 | 0.3336 | 0.9434 |
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+ | 120.6456 | 6.4037 | 11000 | 125.2620 | 0.3606 | 0.3011 | 0.3282 | 0.9430 |
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+ | 120.2335 | 6.6948 | 11500 | 124.5899 | 0.3759 | 0.3466 | 0.3606 | 0.9447 |
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+ | 119.8109 | 6.9859 | 12000 | 123.9922 | 0.3920 | 0.3213 | 0.3532 | 0.9442 |
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+ | 118.4398 | 7.2770 | 12500 | 123.5926 | 0.3971 | 0.3497 | 0.3719 | 0.9455 |
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+ | 117.945 | 7.5680 | 13000 | 123.2072 | 0.4014 | 0.3308 | 0.3627 | 0.9453 |
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+ | 117.9631 | 7.8591 | 13500 | 122.8442 | 0.4017 | 0.3556 | 0.3773 | 0.9458 |
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+ | 117.3963 | 8.1502 | 14000 | 122.6162 | 0.3940 | 0.3769 | 0.3852 | 0.9464 |
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+ | 116.5054 | 8.4413 | 14500 | 122.1343 | 0.4079 | 0.3718 | 0.3890 | 0.9471 |
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+ | 116.5259 | 8.7324 | 15000 | 121.9603 | 0.4158 | 0.3528 | 0.3817 | 0.9470 |
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+ | 116.4213 | 9.0234 | 15500 | 121.8525 | 0.4173 | 0.3718 | 0.3933 | 0.9470 |
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+ | 115.7738 | 9.3145 | 16000 | 121.6751 | 0.4247 | 0.3767 | 0.3993 | 0.9476 |
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+ | 115.8023 | 9.6056 | 16500 | 121.5823 | 0.4306 | 0.3855 | 0.4068 | 0.9479 |
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+ | 115.8227 | 9.8967 | 17000 | 121.6095 | 0.4270 | 0.3784 | 0.4013 | 0.9476 |
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  ### Framework versions
eval_result_ner.json CHANGED
@@ -1 +1 @@
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