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SharonTudi
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DIALOGUE_one

Text Classification
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TensorBoard
Safetensors
distilbert
Generated from Trainer
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End of training

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Files changed (7) hide show
  1. README.md +51 -51
  2. config.json +3 -2
  3. model.safetensors +2 -2
  4. runs/Jan19_11-17-46_eab14bd28cfb/events.out.tfevents.1705663074.eab14bd28cfb.651.7 +3 -0
  5. tokenizer_config.json +1 -1
  6. training_args.bin +1 -1
  7. vocab.txt +0 -0
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:
@@ -18,9 +18,9 @@ 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: 0.1947
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  - Precision: 0.9762
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  - Recall: 0.9737
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  - F1: 0.9736
@@ -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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- | 1.1919 | 0.62 | 30 | 0.8161 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.6182 | 1.25 | 60 | 0.2981 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.2564 | 1.88 | 90 | 0.1427 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0833 | 2.5 | 120 | 0.0918 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0436 | 3.12 | 150 | 0.1185 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0215 | 3.75 | 180 | 0.1243 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0109 | 4.38 | 210 | 0.1179 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0075 | 5.0 | 240 | 0.1240 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0062 | 5.62 | 270 | 0.1362 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0049 | 6.25 | 300 | 0.1385 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0042 | 6.88 | 330 | 0.1572 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0037 | 7.5 | 360 | 0.1569 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0031 | 8.12 | 390 | 0.1501 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0029 | 8.75 | 420 | 0.1563 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0024 | 9.38 | 450 | 0.1617 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0023 | 10.0 | 480 | 0.1625 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0021 | 10.62 | 510 | 0.1658 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.002 | 11.25 | 540 | 0.1699 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0017 | 11.88 | 570 | 0.1727 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0017 | 12.5 | 600 | 0.1731 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0015 | 13.12 | 630 | 0.1756 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0015 | 13.75 | 660 | 0.1764 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0014 | 14.38 | 690 | 0.1797 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0013 | 15.0 | 720 | 0.1817 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0012 | 15.62 | 750 | 0.1822 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0011 | 16.25 | 780 | 0.1833 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0011 | 16.88 | 810 | 0.1843 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.001 | 17.5 | 840 | 0.1857 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.001 | 18.12 | 870 | 0.1872 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0009 | 18.75 | 900 | 0.1884 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0009 | 19.38 | 930 | 0.1879 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0009 | 20.0 | 960 | 0.1882 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0008 | 20.62 | 990 | 0.1888 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0008 | 21.25 | 1020 | 0.1895 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0008 | 21.88 | 1050 | 0.1902 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 22.5 | 1080 | 0.1904 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0008 | 23.12 | 1110 | 0.1911 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 23.75 | 1140 | 0.1919 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 24.38 | 1170 | 0.1923 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 25.0 | 1200 | 0.1928 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 25.62 | 1230 | 0.1933 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 26.25 | 1260 | 0.1938 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 26.88 | 1290 | 0.1939 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 27.5 | 1320 | 0.1943 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0006 | 28.12 | 1350 | 0.1945 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 28.75 | 1380 | 0.1946 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 29.38 | 1410 | 0.1947 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0007 | 30.0 | 1440 | 0.1947 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
106
 
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108
  ### Framework versions
 
1
  ---
2
  license: apache-2.0
3
+ base_model: distilbert-base-cased
4
  tags:
5
  - generated_from_trainer
6
  metrics:
 
18
 
19
  # DIALOGUE_one
20
 
21
+ This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.1862
24
  - Precision: 0.9762
25
  - Recall: 0.9737
26
  - F1: 0.9736
 
55
 
56
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
57
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
58
+ | 1.1763 | 0.62 | 30 | 0.7339 | 0.9083 | 0.8553 | 0.8420 | 0.8553 |
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+ | 0.5684 | 1.25 | 60 | 0.2496 | 0.9524 | 0.9474 | 0.9472 | 0.9474 |
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+ | 0.2445 | 1.88 | 90 | 0.1581 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0728 | 2.5 | 120 | 0.0472 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.038 | 3.12 | 150 | 0.1179 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.012 | 3.75 | 180 | 0.0859 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0065 | 4.38 | 210 | 0.1251 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0046 | 5.0 | 240 | 0.1168 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0034 | 5.62 | 270 | 0.1213 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0028 | 6.25 | 300 | 0.1257 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0025 | 6.88 | 330 | 0.1355 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0022 | 7.5 | 360 | 0.1392 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0019 | 8.12 | 390 | 0.1435 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0016 | 8.75 | 420 | 0.1442 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0014 | 9.38 | 450 | 0.1474 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
73
+ | 0.0013 | 10.0 | 480 | 0.1490 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0012 | 10.62 | 510 | 0.1514 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0011 | 11.25 | 540 | 0.1534 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0011 | 11.88 | 570 | 0.1549 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.001 | 12.5 | 600 | 0.1599 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0009 | 13.12 | 630 | 0.1642 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0009 | 13.75 | 660 | 0.1657 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0008 | 14.38 | 690 | 0.1659 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0008 | 15.0 | 720 | 0.1681 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0007 | 15.62 | 750 | 0.1689 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0007 | 16.25 | 780 | 0.1707 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 16.88 | 810 | 0.1722 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 17.5 | 840 | 0.1720 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 18.12 | 870 | 0.1749 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 18.75 | 900 | 0.1765 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 19.38 | 930 | 0.1774 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 20.0 | 960 | 0.1776 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 20.62 | 990 | 0.1778 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 21.25 | 1020 | 0.1794 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 21.88 | 1050 | 0.1804 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 22.5 | 1080 | 0.1810 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 23.12 | 1110 | 0.1819 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 23.75 | 1140 | 0.1825 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 24.38 | 1170 | 0.1830 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 25.0 | 1200 | 0.1836 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 25.62 | 1230 | 0.1841 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 26.25 | 1260 | 0.1845 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 26.88 | 1290 | 0.1848 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 27.5 | 1320 | 0.1856 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 28.12 | 1350 | 0.1858 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 28.75 | 1380 | 0.1861 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 29.38 | 1410 | 0.1862 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 30.0 | 1440 | 0.1862 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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  ### Framework versions
config.json CHANGED
@@ -1,5 +1,5 @@
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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"
@@ -25,6 +25,7 @@
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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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  "qa_dropout": 0.1,
@@ -33,5 +34,5 @@
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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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  }
 
1
  {
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+ "_name_or_path": "distilbert-base-cased",
3
  "activation": "gelu",
4
  "architectures": [
5
  "DistilBertForSequenceClassification"
 
25
  "model_type": "distilbert",
26
  "n_heads": 12,
27
  "n_layers": 6,
28
+ "output_past": true,
29
  "pad_token_id": 0,
30
  "problem_type": "single_label_classification",
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  "qa_dropout": 0.1,
 
34
  "tie_weights_": true,
35
  "torch_dtype": "float32",
36
  "transformers_version": "4.36.2",
37
+ "vocab_size": 28996
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  }
model.safetensors CHANGED
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runs/Jan19_11-17-46_eab14bd28cfb/events.out.tfevents.1705663074.eab14bd28cfb.651.7 ADDED
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tokenizer_config.json CHANGED
@@ -44,7 +44,7 @@
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  "clean_up_tokenization_spaces": true,
45
  "cls_token": "[CLS]",
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  "do_basic_tokenize": true,
47
- "do_lower_case": true,
48
  "mask_token": "[MASK]",
49
  "model_max_length": 512,
50
  "never_split": null,
 
44
  "clean_up_tokenization_spaces": true,
45
  "cls_token": "[CLS]",
46
  "do_basic_tokenize": true,
47
+ "do_lower_case": false,
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  "mask_token": "[MASK]",
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vocab.txt CHANGED
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