SharonTudi commited on
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End of training

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README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
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  license: apache-2.0
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- base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # DIALOGUE_one
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0122
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- - Precision: 0.8231
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- - Recall: 0.8158
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- - F1: 0.8165
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- - Accuracy: 0.8158
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  ## Model description
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@@ -55,54 +55,54 @@ 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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- | 1.319 | 0.62 | 30 | 1.2219 | 0.6364 | 0.4868 | 0.4265 | 0.4868 |
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- | 0.9623 | 1.25 | 60 | 0.9164 | 0.6857 | 0.6842 | 0.6804 | 0.6842 |
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- | 0.6629 | 1.88 | 90 | 0.6595 | 0.7604 | 0.7237 | 0.7224 | 0.7237 |
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- | 0.5046 | 2.5 | 120 | 0.5740 | 0.7927 | 0.7763 | 0.7760 | 0.7763 |
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- | 0.3602 | 3.12 | 150 | 0.6172 | 0.7636 | 0.7632 | 0.7621 | 0.7632 |
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- | 0.2774 | 3.75 | 180 | 0.6772 | 0.7717 | 0.7632 | 0.7645 | 0.7632 |
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- | 0.3058 | 4.38 | 210 | 0.6732 | 0.7974 | 0.7632 | 0.7632 | 0.7632 |
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- | 0.2064 | 5.0 | 240 | 0.7566 | 0.7947 | 0.7632 | 0.7534 | 0.7632 |
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- | 0.1447 | 5.62 | 270 | 0.6615 | 0.7908 | 0.7895 | 0.7892 | 0.7895 |
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- | 0.1764 | 6.25 | 300 | 0.6646 | 0.7908 | 0.7895 | 0.7892 | 0.7895 |
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- | 0.1059 | 6.88 | 330 | 0.6377 | 0.8522 | 0.8421 | 0.8417 | 0.8421 |
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- | 0.0871 | 7.5 | 360 | 0.6075 | 0.8311 | 0.8289 | 0.8286 | 0.8289 |
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- | 0.0861 | 8.12 | 390 | 0.6845 | 0.8484 | 0.8421 | 0.8410 | 0.8421 |
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- | 0.0693 | 8.75 | 420 | 0.6484 | 0.8598 | 0.8553 | 0.8553 | 0.8553 |
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- | 0.0481 | 9.38 | 450 | 0.6957 | 0.8469 | 0.8421 | 0.8419 | 0.8421 |
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- | 0.0405 | 10.0 | 480 | 0.7195 | 0.8598 | 0.8553 | 0.8553 | 0.8553 |
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- | 0.039 | 10.62 | 510 | 0.8293 | 0.8548 | 0.8421 | 0.8442 | 0.8421 |
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- | 0.0441 | 11.25 | 540 | 0.7293 | 0.8598 | 0.8553 | 0.8553 | 0.8553 |
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- | 0.0203 | 11.88 | 570 | 0.8127 | 0.8530 | 0.8421 | 0.8437 | 0.8421 |
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- | 0.0207 | 12.5 | 600 | 0.8381 | 0.8482 | 0.8421 | 0.8415 | 0.8421 |
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- | 0.0183 | 13.12 | 630 | 0.7808 | 0.8598 | 0.8553 | 0.8553 | 0.8553 |
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- | 0.0184 | 13.75 | 660 | 0.8203 | 0.8486 | 0.8421 | 0.8414 | 0.8421 |
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- | 0.0178 | 14.38 | 690 | 0.8099 | 0.8598 | 0.8553 | 0.8553 | 0.8553 |
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- | 0.009 | 15.0 | 720 | 0.8476 | 0.8469 | 0.8421 | 0.8425 | 0.8421 |
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- | 0.0029 | 15.62 | 750 | 0.8834 | 0.8375 | 0.8289 | 0.8291 | 0.8289 |
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- | 0.0126 | 16.25 | 780 | 0.9205 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0026 | 16.88 | 810 | 0.9224 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0024 | 17.5 | 840 | 0.8937 | 0.8469 | 0.8421 | 0.8425 | 0.8421 |
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- | 0.0029 | 18.12 | 870 | 1.0012 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0021 | 18.75 | 900 | 0.9384 | 0.7969 | 0.7895 | 0.7912 | 0.7895 |
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- | 0.0019 | 19.38 | 930 | 0.9420 | 0.8097 | 0.8026 | 0.8039 | 0.8026 |
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- | 0.0019 | 20.0 | 960 | 0.9681 | 0.7969 | 0.7895 | 0.7912 | 0.7895 |
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- | 0.0018 | 20.62 | 990 | 0.9838 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0016 | 21.25 | 1020 | 0.9798 | 0.7969 | 0.7895 | 0.7912 | 0.7895 |
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- | 0.0016 | 21.88 | 1050 | 0.9765 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0014 | 22.5 | 1080 | 0.9906 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0014 | 23.12 | 1110 | 0.9857 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0015 | 23.75 | 1140 | 1.0050 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0013 | 24.38 | 1170 | 1.0049 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0013 | 25.0 | 1200 | 1.0078 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0013 | 25.62 | 1230 | 1.0083 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0012 | 26.25 | 1260 | 1.0051 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0013 | 26.88 | 1290 | 1.0121 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0012 | 27.5 | 1320 | 1.0127 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0012 | 28.12 | 1350 | 1.0134 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0012 | 28.75 | 1380 | 1.0119 | 0.8347 | 0.8289 | 0.8296 | 0.8289 |
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- | 0.0012 | 29.38 | 1410 | 1.0122 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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- | 0.0012 | 30.0 | 1440 | 1.0122 | 0.8231 | 0.8158 | 0.8165 | 0.8158 |
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  ### Framework versions
 
1
  ---
2
  license: apache-2.0
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+ base_model: bert-base-cased
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  tags:
5
  - generated_from_trainer
6
  metrics:
 
18
 
19
  # DIALOGUE_one
20
 
21
+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
22
  It achieves the following results on the evaluation set:
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+ - Loss: 1.4205
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+ - Precision: 0.7375
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+ - Recall: 0.7368
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+ - F1: 0.7345
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+ - Accuracy: 0.7368
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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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+ | 1.2687 | 0.62 | 30 | 1.0661 | 0.7208 | 0.6184 | 0.6068 | 0.6184 |
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+ | 0.7981 | 1.25 | 60 | 0.6953 | 0.8047 | 0.7895 | 0.7941 | 0.7895 |
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+ | 0.5436 | 1.88 | 90 | 0.5773 | 0.8362 | 0.7632 | 0.7502 | 0.7632 |
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+ | 0.4194 | 2.5 | 120 | 0.5654 | 0.7821 | 0.7632 | 0.7620 | 0.7632 |
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+ | 0.3344 | 3.12 | 150 | 0.6244 | 0.7686 | 0.7632 | 0.7634 | 0.7632 |
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+ | 0.2455 | 3.75 | 180 | 0.5157 | 0.8687 | 0.8421 | 0.8422 | 0.8421 |
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+ | 0.2549 | 4.38 | 210 | 0.6403 | 0.8533 | 0.8289 | 0.8298 | 0.8289 |
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+ | 0.1941 | 5.0 | 240 | 0.8651 | 0.7571 | 0.75 | 0.7461 | 0.75 |
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+ | 0.1621 | 5.62 | 270 | 0.7141 | 0.7793 | 0.7763 | 0.7765 | 0.7763 |
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+ | 0.1514 | 6.25 | 300 | 0.5450 | 0.8961 | 0.8684 | 0.8698 | 0.8684 |
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+ | 0.0772 | 6.88 | 330 | 0.8617 | 0.7966 | 0.7895 | 0.7923 | 0.7895 |
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+ | 0.065 | 7.5 | 360 | 0.7816 | 0.7632 | 0.7632 | 0.7618 | 0.7632 |
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+ | 0.0676 | 8.12 | 390 | 0.7294 | 0.7947 | 0.7895 | 0.7918 | 0.7895 |
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+ | 0.048 | 8.75 | 420 | 0.8226 | 0.8417 | 0.8421 | 0.8400 | 0.8421 |
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+ | 0.0377 | 9.38 | 450 | 1.1197 | 0.7021 | 0.7105 | 0.7030 | 0.7105 |
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+ | 0.0175 | 10.0 | 480 | 1.1080 | 0.7892 | 0.7895 | 0.7811 | 0.7895 |
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+ | 0.0169 | 10.62 | 510 | 1.1289 | 0.7337 | 0.7368 | 0.7331 | 0.7368 |
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+ | 0.0028 | 11.25 | 540 | 1.1263 | 0.7243 | 0.7237 | 0.7184 | 0.7237 |
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+ | 0.0023 | 11.88 | 570 | 1.2298 | 0.7103 | 0.7105 | 0.7042 | 0.7105 |
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+ | 0.0019 | 12.5 | 600 | 1.2863 | 0.7103 | 0.7105 | 0.7042 | 0.7105 |
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+ | 0.0017 | 13.12 | 630 | 1.2531 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0016 | 13.75 | 660 | 1.3108 | 0.7103 | 0.7105 | 0.7042 | 0.7105 |
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+ | 0.0015 | 14.38 | 690 | 1.3185 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0014 | 15.0 | 720 | 1.3296 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0012 | 15.62 | 750 | 1.3296 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0012 | 16.25 | 780 | 1.3300 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0012 | 16.88 | 810 | 1.2730 | 0.7677 | 0.7632 | 0.7640 | 0.7632 |
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+ | 0.0011 | 17.5 | 840 | 1.2823 | 0.7677 | 0.7632 | 0.7640 | 0.7632 |
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+ | 0.0011 | 18.12 | 870 | 1.3328 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.001 | 18.75 | 900 | 1.3341 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.001 | 19.38 | 930 | 1.3587 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0009 | 20.0 | 960 | 1.3728 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0009 | 20.62 | 990 | 1.3904 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 21.25 | 1020 | 1.3928 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 21.88 | 1050 | 1.3913 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 22.5 | 1080 | 1.3853 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 23.12 | 1110 | 1.3900 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 23.75 | 1140 | 1.3935 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 24.38 | 1170 | 1.4068 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 25.0 | 1200 | 1.4144 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 25.62 | 1230 | 1.4106 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0008 | 26.25 | 1260 | 1.4165 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 26.88 | 1290 | 1.4207 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 27.5 | 1320 | 1.4236 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 28.12 | 1350 | 1.4281 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 28.75 | 1380 | 1.4204 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 29.38 | 1410 | 1.4213 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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+ | 0.0007 | 30.0 | 1440 | 1.4205 | 0.7375 | 0.7368 | 0.7345 | 0.7368 |
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  ### Framework versions
config.json CHANGED
@@ -1,13 +1,14 @@
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  {
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- "_name_or_path": "distilbert-base-uncased",
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- "activation": "gelu",
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  "architectures": [
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- "DistilBertForSequenceClassification"
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  ],
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- "attention_dropout": 0.1,
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- "dim": 768,
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- "dropout": 0.1,
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- "hidden_dim": 3072,
 
 
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  "id2label": {
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  "0": "Hospital-Inform",
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  "1": "Hospital-Request",
@@ -15,23 +16,24 @@
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  "3": "general-thank"
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  },
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  "initializer_range": 0.02,
 
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- "model_type": "distilbert",
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- "n_heads": 12,
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- "n_layers": 6,
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  "pad_token_id": 0,
 
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  "problem_type": "single_label_classification",
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- "sinusoidal_pos_embds": false,
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- "tie_weights_": true,
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  "torch_dtype": "float32",
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  "transformers_version": "4.36.2",
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- "vocab_size": 30522
 
 
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  }
 
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  {
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+ "_name_or_path": "bert-base-cased",
 
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  "architectures": [
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+ "BertForSequenceClassification"
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+ "hidden_size": 768,
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  "id2label": {
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  "0": "Hospital-Inform",
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  "1": "Hospital-Request",
 
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  "3": "general-thank"
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  },
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  "initializer_range": 0.02,
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+ "num_hidden_layers": 12,
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  "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
 
 
 
 
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  "torch_dtype": "float32",
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  "transformers_version": "4.36.2",
36
+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 28996
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@@ -52,6 +52,6 @@
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  "tokenize_chinese_chars": true,
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