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--- |
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license: apache-2.0 |
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base_model: distilbert-base-cased |
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tags: |
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- generated_from_trainer |
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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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model-index: |
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- name: DIALOGUE_one |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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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-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: 0.2052 |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 1.2045 | 0.62 | 30 | 0.7843 | 0.9565 | 0.9474 | 0.9468 | 0.9474 | |
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| 0.5845 | 1.25 | 60 | 0.2507 | 0.9524 | 0.9474 | 0.9472 | 0.9474 | |
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| 0.23 | 1.88 | 90 | 0.1376 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0722 | 2.5 | 120 | 0.0647 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0515 | 3.12 | 150 | 0.1376 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0197 | 3.75 | 180 | 0.1505 | 0.9637 | 0.9605 | 0.9604 | 0.9605 | |
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| 0.0065 | 4.38 | 210 | 0.1456 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0046 | 5.0 | 240 | 0.1376 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0037 | 5.62 | 270 | 0.1569 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0028 | 6.25 | 300 | 0.1551 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0024 | 6.88 | 330 | 0.1594 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0022 | 7.5 | 360 | 0.1624 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0018 | 8.12 | 390 | 0.1687 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0016 | 8.75 | 420 | 0.1698 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0014 | 9.38 | 450 | 0.1732 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0013 | 10.0 | 480 | 0.1741 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0012 | 10.62 | 510 | 0.1772 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0011 | 11.25 | 540 | 0.1791 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.001 | 11.88 | 570 | 0.1814 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.001 | 12.5 | 600 | 0.1840 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0008 | 13.12 | 630 | 0.1858 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0009 | 13.75 | 660 | 0.1877 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0008 | 14.38 | 690 | 0.1893 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0007 | 15.0 | 720 | 0.1902 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0007 | 15.62 | 750 | 0.1908 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0007 | 16.25 | 780 | 0.1931 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0006 | 16.88 | 810 | 0.1936 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0006 | 17.5 | 840 | 0.1946 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0006 | 18.12 | 870 | 0.1961 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0006 | 18.75 | 900 | 0.1966 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 19.38 | 930 | 0.1965 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 20.0 | 960 | 0.1968 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 20.62 | 990 | 0.1974 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 21.25 | 1020 | 0.1987 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 21.88 | 1050 | 0.1995 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 22.5 | 1080 | 0.2001 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0005 | 23.12 | 1110 | 0.2010 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 23.75 | 1140 | 0.2018 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 24.38 | 1170 | 0.2021 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 25.0 | 1200 | 0.2025 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 25.62 | 1230 | 0.2034 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 26.25 | 1260 | 0.2038 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 26.88 | 1290 | 0.2042 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 27.5 | 1320 | 0.2047 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 28.12 | 1350 | 0.2048 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 28.75 | 1380 | 0.2050 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 29.38 | 1410 | 0.2051 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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| 0.0004 | 30.0 | 1440 | 0.2052 | 0.9762 | 0.9737 | 0.9736 | 0.9737 | |
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### Framework versions |
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- Transformers 4.37.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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