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SharonTudi
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DIALOGUE_one

Text Classification
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Safetensors
distilbert
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End of training

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Files changed (5) hide show
  1. README.md +54 -54
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Jan22_11-29-54_e51572f30c70/events.out.tfevents.1705923042.e51572f30c70.565.0 +3 -0
  5. training_args.bin +1 -1
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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4205
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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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@@ -55,59 +55,59 @@ 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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- | 1.2687 | 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
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- - Transformers 4.36.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1156
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+ - Precision: 0.9762
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+ - Recall: 0.9737
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+ - F1: 0.9736
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+ - Accuracy: 0.9737
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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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+ | 1.1326 | 0.62 | 30 | 0.6327 | 0.9875 | 0.9868 | 0.9868 | 0.9868 |
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+ | 0.4421 | 1.25 | 60 | 0.1854 | 0.9637 | 0.9605 | 0.9604 | 0.9605 |
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+ | 0.1449 | 1.88 | 90 | 0.0766 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0179 | 2.5 | 120 | 0.0802 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0059 | 3.12 | 150 | 0.0361 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0032 | 3.75 | 180 | 0.0472 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0035 | 4.38 | 210 | 0.0995 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0018 | 5.0 | 240 | 0.0930 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0015 | 5.62 | 270 | 0.0957 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0013 | 6.25 | 300 | 0.0991 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0012 | 6.88 | 330 | 0.1028 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.001 | 7.5 | 360 | 0.0992 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0009 | 8.12 | 390 | 0.1020 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0009 | 8.75 | 420 | 0.1037 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0008 | 9.38 | 450 | 0.1037 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0007 | 10.0 | 480 | 0.1035 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0007 | 10.62 | 510 | 0.1044 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 11.25 | 540 | 0.1063 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 11.88 | 570 | 0.1061 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 12.5 | 600 | 0.1071 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 13.12 | 630 | 0.1057 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 13.75 | 660 | 0.1064 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 14.38 | 690 | 0.1072 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 15.0 | 720 | 0.1063 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 15.62 | 750 | 0.1068 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 16.25 | 780 | 0.1090 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 16.88 | 810 | 0.1085 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 17.5 | 840 | 0.1095 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 18.12 | 870 | 0.1106 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 18.75 | 900 | 0.1110 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 19.38 | 930 | 0.1101 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 20.0 | 960 | 0.1110 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 20.62 | 990 | 0.1116 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 21.25 | 1020 | 0.1121 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 21.88 | 1050 | 0.1126 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 22.5 | 1080 | 0.1117 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 23.12 | 1110 | 0.1127 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 23.75 | 1140 | 0.1135 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 24.38 | 1170 | 0.1138 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 25.0 | 1200 | 0.1145 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 25.62 | 1230 | 0.1151 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 26.25 | 1260 | 0.1151 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 26.88 | 1290 | 0.1148 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 27.5 | 1320 | 0.1152 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 28.12 | 1350 | 0.1153 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 28.75 | 1380 | 0.1156 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 29.38 | 1410 | 0.1156 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 30.0 | 1440 | 0.1156 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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  ### Framework versions
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+ - Transformers 4.37.0
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
config.json CHANGED
@@ -32,7 +32,7 @@
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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",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 28996
 
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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": "4.37.0",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 28996
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