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distilbert
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End of training

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  1. README.md +34 -34
  2. model.safetensors +1 -1
  3. runs/Apr04_12-24-34_76de971d69be/events.out.tfevents.1712240723.76de971d69be.181.3 +2 -2
  4. runs/Apr04_12-24-34_76de971d69be/events.out.tfevents.1712247661.76de971d69be.181.4 +3 -0
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8043
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- - Precision: 0.8432
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- - Recall: 0.8375
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- - F1: 0.8381
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- - Accuracy: 0.8375
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  ## Model description
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@@ -55,35 +55,35 @@ 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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- | 1.9232 | 0.14 | 30 | 1.8330 | 0.2755 | 0.2773 | 0.2340 | 0.2773 |
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- | 1.7293 | 0.27 | 60 | 1.4729 | 0.3588 | 0.3613 | 0.2487 | 0.3613 |
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- | 1.3897 | 0.41 | 90 | 1.2344 | 0.6697 | 0.5238 | 0.4653 | 0.5238 |
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- | 1.2399 | 0.54 | 120 | 1.1505 | 0.6705 | 0.6106 | 0.5897 | 0.6106 |
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- | 1.1299 | 0.68 | 150 | 0.8937 | 0.7178 | 0.7087 | 0.7062 | 0.7087 |
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- | 0.9878 | 0.81 | 180 | 0.8656 | 0.7067 | 0.6583 | 0.6466 | 0.6583 |
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- | 0.7844 | 0.95 | 210 | 0.7538 | 0.7501 | 0.7339 | 0.7321 | 0.7339 |
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- | 0.5865 | 1.08 | 240 | 0.7162 | 0.7628 | 0.7563 | 0.7559 | 0.7563 |
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- | 0.4725 | 1.22 | 270 | 0.7242 | 0.8196 | 0.7815 | 0.7836 | 0.7815 |
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- | 0.4168 | 1.35 | 300 | 0.6477 | 0.8091 | 0.7983 | 0.8001 | 0.7983 |
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- | 0.3725 | 1.49 | 330 | 0.5628 | 0.7972 | 0.7871 | 0.7872 | 0.7871 |
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- | 0.3664 | 1.62 | 360 | 0.6316 | 0.8052 | 0.7955 | 0.7957 | 0.7955 |
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- | 0.3654 | 1.76 | 390 | 0.6254 | 0.8246 | 0.8179 | 0.8177 | 0.8179 |
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- | 0.2986 | 1.89 | 420 | 0.6129 | 0.8150 | 0.8095 | 0.8098 | 0.8095 |
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- | 0.2652 | 2.03 | 450 | 0.6471 | 0.8190 | 0.8151 | 0.8151 | 0.8151 |
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- | 0.1143 | 2.16 | 480 | 0.6956 | 0.8349 | 0.8291 | 0.8262 | 0.8291 |
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- | 0.0961 | 2.3 | 510 | 0.7992 | 0.8205 | 0.8179 | 0.8170 | 0.8179 |
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- | 0.1593 | 2.43 | 540 | 0.7508 | 0.8296 | 0.8207 | 0.8210 | 0.8207 |
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- | 0.1486 | 2.57 | 570 | 0.7732 | 0.8262 | 0.8207 | 0.8203 | 0.8207 |
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- | 0.1515 | 2.7 | 600 | 0.7413 | 0.8362 | 0.8319 | 0.8321 | 0.8319 |
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- | 0.0922 | 2.84 | 630 | 0.7168 | 0.8416 | 0.8375 | 0.8375 | 0.8375 |
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- | 0.1195 | 2.97 | 660 | 0.7461 | 0.8436 | 0.8347 | 0.8357 | 0.8347 |
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- | 0.0882 | 3.11 | 690 | 0.7472 | 0.8404 | 0.8319 | 0.8321 | 0.8319 |
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- | 0.0573 | 3.24 | 720 | 0.7631 | 0.8409 | 0.8347 | 0.8356 | 0.8347 |
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- | 0.0284 | 3.38 | 750 | 0.7559 | 0.8346 | 0.8319 | 0.8321 | 0.8319 |
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- | 0.0307 | 3.51 | 780 | 0.7669 | 0.8425 | 0.8375 | 0.8379 | 0.8375 |
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- | 0.0225 | 3.65 | 810 | 0.7827 | 0.8428 | 0.8375 | 0.8380 | 0.8375 |
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- | 0.0512 | 3.78 | 840 | 0.8073 | 0.8444 | 0.8375 | 0.8381 | 0.8375 |
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- | 0.0261 | 3.92 | 870 | 0.8061 | 0.8412 | 0.8347 | 0.8354 | 0.8347 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3385
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+ - Precision: 0.8173
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+ - Recall: 0.8123
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+ - F1: 0.8128
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+ - Accuracy: 0.8123
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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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+ | 0.0142 | 0.14 | 30 | 0.9604 | 0.8284 | 0.8207 | 0.8202 | 0.8207 |
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+ | 0.0446 | 0.27 | 60 | 0.9032 | 0.8403 | 0.8347 | 0.8353 | 0.8347 |
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+ | 0.0995 | 0.41 | 90 | 1.0133 | 0.8310 | 0.8263 | 0.8258 | 0.8263 |
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+ | 0.0776 | 0.54 | 120 | 1.1968 | 0.8130 | 0.7983 | 0.7961 | 0.7983 |
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+ | 0.0517 | 0.68 | 150 | 1.1238 | 0.8363 | 0.8263 | 0.8263 | 0.8263 |
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+ | 0.1014 | 0.81 | 180 | 1.0750 | 0.8334 | 0.8291 | 0.8293 | 0.8291 |
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+ | 0.1166 | 0.95 | 210 | 1.1253 | 0.8009 | 0.7955 | 0.7955 | 0.7955 |
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+ | 0.0447 | 1.08 | 240 | 1.2334 | 0.7969 | 0.7899 | 0.7883 | 0.7899 |
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+ | 0.0411 | 1.22 | 270 | 1.1707 | 0.8369 | 0.8319 | 0.8324 | 0.8319 |
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+ | 0.1145 | 1.35 | 300 | 1.3773 | 0.8320 | 0.8039 | 0.8021 | 0.8039 |
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+ | 0.06 | 1.49 | 330 | 1.1480 | 0.8320 | 0.8291 | 0.8274 | 0.8291 |
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+ | 0.0622 | 1.62 | 360 | 1.0856 | 0.8252 | 0.8235 | 0.8235 | 0.8235 |
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+ | 0.0366 | 1.76 | 390 | 1.2860 | 0.8236 | 0.8151 | 0.8162 | 0.8151 |
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+ | 0.0565 | 1.89 | 420 | 1.2558 | 0.8116 | 0.8011 | 0.8024 | 0.8011 |
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+ | 0.0019 | 2.03 | 450 | 1.2740 | 0.8208 | 0.8179 | 0.8180 | 0.8179 |
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+ | 0.0024 | 2.16 | 480 | 1.3075 | 0.8201 | 0.8151 | 0.8155 | 0.8151 |
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+ | 0.024 | 2.3 | 510 | 1.3170 | 0.8188 | 0.8151 | 0.8154 | 0.8151 |
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+ | 0.0008 | 2.43 | 540 | 1.3992 | 0.8099 | 0.8011 | 0.8024 | 0.8011 |
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+ | 0.0445 | 2.57 | 570 | 1.2633 | 0.8237 | 0.8207 | 0.8209 | 0.8207 |
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+ | 0.01 | 2.7 | 600 | 1.2843 | 0.8270 | 0.8235 | 0.8235 | 0.8235 |
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+ | 0.0175 | 2.84 | 630 | 1.2997 | 0.8246 | 0.8207 | 0.8208 | 0.8207 |
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+ | 0.0111 | 2.97 | 660 | 1.3486 | 0.8147 | 0.8095 | 0.8099 | 0.8095 |
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+ | 0.0006 | 3.11 | 690 | 1.3543 | 0.8154 | 0.8123 | 0.8120 | 0.8123 |
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+ | 0.0005 | 3.24 | 720 | 1.3493 | 0.8185 | 0.8151 | 0.8148 | 0.8151 |
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+ | 0.0129 | 3.38 | 750 | 1.3294 | 0.8136 | 0.8095 | 0.8098 | 0.8095 |
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+ | 0.0005 | 3.51 | 780 | 1.3441 | 0.8143 | 0.8095 | 0.8100 | 0.8095 |
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+ | 0.0005 | 3.65 | 810 | 1.3428 | 0.8143 | 0.8095 | 0.8100 | 0.8095 |
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+ | 0.0005 | 3.78 | 840 | 1.3402 | 0.8173 | 0.8123 | 0.8128 | 0.8123 |
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+ | 0.0005 | 3.92 | 870 | 1.3395 | 0.8173 | 0.8123 | 0.8128 | 0.8123 |
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  ### Framework versions
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