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--- |
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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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model-index: |
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- name: unt_faqs_model |
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results: [] |
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language: |
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- en |
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pipeline_tag: question-answering |
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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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# unt_faqs_model |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.1017 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 12 | 5.4252 | |
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| No log | 2.0 | 24 | 4.4929 | |
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| No log | 3.0 | 36 | 3.8593 | |
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| No log | 4.0 | 48 | 3.1898 | |
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| No log | 5.0 | 60 | 3.2708 | |
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| No log | 6.0 | 72 | 3.2766 | |
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| No log | 7.0 | 84 | 3.6022 | |
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| No log | 8.0 | 96 | 3.8336 | |
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| No log | 9.0 | 108 | 4.0215 | |
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| No log | 10.0 | 120 | 4.1909 | |
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| No log | 11.0 | 132 | 4.4297 | |
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| No log | 12.0 | 144 | 4.3085 | |
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| No log | 13.0 | 156 | 4.4102 | |
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| No log | 14.0 | 168 | 4.4956 | |
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| No log | 15.0 | 180 | 4.8586 | |
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| No log | 16.0 | 192 | 4.8999 | |
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| No log | 17.0 | 204 | 4.6935 | |
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| No log | 18.0 | 216 | 4.5933 | |
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| No log | 19.0 | 228 | 4.5490 | |
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| No log | 20.0 | 240 | 4.7068 | |
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| No log | 21.0 | 252 | 4.7150 | |
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| No log | 22.0 | 264 | 4.9225 | |
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| No log | 23.0 | 276 | 4.7852 | |
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| No log | 24.0 | 288 | 4.8968 | |
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| No log | 25.0 | 300 | 4.9657 | |
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| No log | 26.0 | 312 | 5.0764 | |
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| No log | 27.0 | 324 | 5.0940 | |
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| No log | 28.0 | 336 | 5.1408 | |
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| No log | 29.0 | 348 | 5.3001 | |
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| No log | 30.0 | 360 | 5.1304 | |
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| No log | 31.0 | 372 | 5.4316 | |
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| No log | 32.0 | 384 | 5.3884 | |
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| No log | 33.0 | 396 | 5.4434 | |
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| No log | 34.0 | 408 | 5.3642 | |
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| No log | 35.0 | 420 | 5.5924 | |
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| No log | 36.0 | 432 | 5.2098 | |
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| No log | 37.0 | 444 | 5.3167 | |
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| No log | 38.0 | 456 | 5.2808 | |
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| No log | 39.0 | 468 | 5.3687 | |
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| No log | 40.0 | 480 | 5.4625 | |
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| No log | 41.0 | 492 | 5.4122 | |
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| 0.6438 | 42.0 | 504 | 5.4850 | |
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| 0.6438 | 43.0 | 516 | 5.4797 | |
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| 0.6438 | 44.0 | 528 | 5.8061 | |
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| 0.6438 | 45.0 | 540 | 5.8501 | |
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| 0.6438 | 46.0 | 552 | 5.6079 | |
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| 0.6438 | 47.0 | 564 | 5.6625 | |
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| 0.6438 | 48.0 | 576 | 5.7005 | |
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| 0.6438 | 49.0 | 588 | 5.6703 | |
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| 0.6438 | 50.0 | 600 | 5.5704 | |
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| 0.6438 | 51.0 | 612 | 5.7556 | |
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| 0.6438 | 52.0 | 624 | 5.6541 | |
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| 0.6438 | 53.0 | 636 | 5.7571 | |
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| 0.6438 | 54.0 | 648 | 5.8092 | |
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| 0.6438 | 55.0 | 660 | 5.8529 | |
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| 0.6438 | 56.0 | 672 | 5.7974 | |
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| 0.6438 | 57.0 | 684 | 6.0617 | |
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| 0.6438 | 58.0 | 696 | 5.8630 | |
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| 0.6438 | 59.0 | 708 | 5.8652 | |
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| 0.6438 | 60.0 | 720 | 5.9569 | |
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| 0.6438 | 61.0 | 732 | 6.0163 | |
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| 0.6438 | 62.0 | 744 | 5.8635 | |
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| 0.6438 | 63.0 | 756 | 6.1112 | |
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| 0.6438 | 64.0 | 768 | 5.9750 | |
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| 0.6438 | 65.0 | 780 | 5.7267 | |
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| 0.6438 | 66.0 | 792 | 5.9968 | |
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| 0.6438 | 67.0 | 804 | 5.9974 | |
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| 0.6438 | 68.0 | 816 | 5.9145 | |
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| 0.6438 | 69.0 | 828 | 5.8521 | |
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| 0.6438 | 70.0 | 840 | 5.9012 | |
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| 0.6438 | 71.0 | 852 | 5.9272 | |
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| 0.6438 | 72.0 | 864 | 5.9137 | |
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| 0.6438 | 73.0 | 876 | 5.9371 | |
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| 0.6438 | 74.0 | 888 | 5.9811 | |
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| 0.6438 | 75.0 | 900 | 6.0054 | |
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| 0.6438 | 76.0 | 912 | 6.0101 | |
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| 0.6438 | 77.0 | 924 | 6.0301 | |
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| 0.6438 | 78.0 | 936 | 5.9783 | |
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| 0.6438 | 79.0 | 948 | 5.9784 | |
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| 0.6438 | 80.0 | 960 | 6.0630 | |
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| 0.6438 | 81.0 | 972 | 6.1151 | |
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| 0.6438 | 82.0 | 984 | 6.0869 | |
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| 0.6438 | 83.0 | 996 | 6.0823 | |
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| 0.0228 | 84.0 | 1008 | 6.0805 | |
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| 0.0228 | 85.0 | 1020 | 6.0722 | |
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| 0.0228 | 86.0 | 1032 | 6.0623 | |
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| 0.0228 | 87.0 | 1044 | 6.0561 | |
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| 0.0228 | 88.0 | 1056 | 6.0367 | |
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| 0.0228 | 89.0 | 1068 | 6.0342 | |
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| 0.0228 | 90.0 | 1080 | 6.0461 | |
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| 0.0228 | 91.0 | 1092 | 6.0646 | |
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| 0.0228 | 92.0 | 1104 | 6.0780 | |
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| 0.0228 | 93.0 | 1116 | 6.0926 | |
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| 0.0228 | 94.0 | 1128 | 6.0963 | |
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| 0.0228 | 95.0 | 1140 | 6.1009 | |
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| 0.0228 | 96.0 | 1152 | 6.1044 | |
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| 0.0228 | 97.0 | 1164 | 6.1015 | |
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| 0.0228 | 98.0 | 1176 | 6.1014 | |
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| 0.0228 | 99.0 | 1188 | 6.1021 | |
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| 0.0228 | 100.0 | 1200 | 6.1017 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.1+cpu |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
