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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: rh_qa_model |
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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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# rh_qa_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: 0.4148 |
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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 | 14 | 3.1715 | |
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| No log | 2.0 | 28 | 2.2625 | |
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| No log | 3.0 | 42 | 1.8385 | |
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| No log | 4.0 | 56 | 1.5586 | |
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| No log | 5.0 | 70 | 1.3127 | |
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| No log | 6.0 | 84 | 1.1556 | |
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| No log | 7.0 | 98 | 1.0699 | |
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| No log | 8.0 | 112 | 0.8843 | |
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| No log | 9.0 | 126 | 0.7782 | |
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| No log | 10.0 | 140 | 0.8645 | |
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| No log | 11.0 | 154 | 0.6969 | |
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| No log | 12.0 | 168 | 0.7130 | |
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| No log | 13.0 | 182 | 0.7346 | |
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| No log | 14.0 | 196 | 0.6394 | |
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| No log | 15.0 | 210 | 0.6501 | |
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| No log | 16.0 | 224 | 0.5198 | |
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| No log | 17.0 | 238 | 0.6806 | |
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| No log | 18.0 | 252 | 0.5010 | |
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| No log | 19.0 | 266 | 0.4730 | |
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| No log | 20.0 | 280 | 0.4384 | |
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| No log | 21.0 | 294 | 0.5072 | |
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| No log | 22.0 | 308 | 0.7052 | |
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| No log | 23.0 | 322 | 0.5192 | |
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| No log | 24.0 | 336 | 0.5131 | |
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| No log | 25.0 | 350 | 0.4587 | |
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| No log | 26.0 | 364 | 0.5063 | |
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| No log | 27.0 | 378 | 0.5847 | |
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| No log | 28.0 | 392 | 0.5687 | |
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| No log | 29.0 | 406 | 0.4751 | |
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| No log | 30.0 | 420 | 0.5268 | |
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| No log | 31.0 | 434 | 0.4624 | |
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| No log | 32.0 | 448 | 0.6690 | |
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| No log | 33.0 | 462 | 0.5542 | |
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| No log | 34.0 | 476 | 0.5325 | |
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| No log | 35.0 | 490 | 0.4658 | |
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| 0.6171 | 36.0 | 504 | 0.4740 | |
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| 0.6171 | 37.0 | 518 | 0.4895 | |
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| 0.6171 | 38.0 | 532 | 0.4703 | |
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| 0.6171 | 39.0 | 546 | 0.5297 | |
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| 0.6171 | 40.0 | 560 | 0.4644 | |
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| 0.6171 | 41.0 | 574 | 0.4785 | |
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| 0.6171 | 42.0 | 588 | 0.4762 | |
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| 0.6171 | 43.0 | 602 | 0.4621 | |
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| 0.6171 | 44.0 | 616 | 0.5370 | |
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| 0.6171 | 45.0 | 630 | 0.5178 | |
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| 0.6171 | 46.0 | 644 | 0.4732 | |
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| 0.6171 | 47.0 | 658 | 0.4982 | |
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| 0.6171 | 48.0 | 672 | 0.4894 | |
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| 0.6171 | 49.0 | 686 | 0.4453 | |
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| 0.6171 | 50.0 | 700 | 0.5137 | |
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| 0.6171 | 51.0 | 714 | 0.4349 | |
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| 0.6171 | 52.0 | 728 | 0.4134 | |
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| 0.6171 | 53.0 | 742 | 0.4375 | |
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| 0.6171 | 54.0 | 756 | 0.4453 | |
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| 0.6171 | 55.0 | 770 | 0.4425 | |
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| 0.6171 | 56.0 | 784 | 0.3920 | |
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| 0.6171 | 57.0 | 798 | 0.3902 | |
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| 0.6171 | 58.0 | 812 | 0.4387 | |
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| 0.6171 | 59.0 | 826 | 0.4759 | |
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| 0.6171 | 60.0 | 840 | 0.4824 | |
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| 0.6171 | 61.0 | 854 | 0.4481 | |
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| 0.6171 | 62.0 | 868 | 0.4206 | |
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| 0.6171 | 63.0 | 882 | 0.4524 | |
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| 0.6171 | 64.0 | 896 | 0.3694 | |
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| 0.6171 | 65.0 | 910 | 0.4345 | |
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| 0.6171 | 66.0 | 924 | 0.4957 | |
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| 0.6171 | 67.0 | 938 | 0.4407 | |
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| 0.6171 | 68.0 | 952 | 0.4615 | |
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| 0.6171 | 69.0 | 966 | 0.4300 | |
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| 0.6171 | 70.0 | 980 | 0.4805 | |
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| 0.6171 | 71.0 | 994 | 0.4524 | |
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| 0.2178 | 72.0 | 1008 | 0.4411 | |
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| 0.2178 | 73.0 | 1022 | 0.3767 | |
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| 0.2178 | 74.0 | 1036 | 0.4178 | |
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| 0.2178 | 75.0 | 1050 | 0.4271 | |
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| 0.2178 | 76.0 | 1064 | 0.4397 | |
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| 0.2178 | 77.0 | 1078 | 0.4461 | |
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| 0.2178 | 78.0 | 1092 | 0.4313 | |
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| 0.2178 | 79.0 | 1106 | 0.4162 | |
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| 0.2178 | 80.0 | 1120 | 0.4404 | |
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| 0.2178 | 81.0 | 1134 | 0.4549 | |
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| 0.2178 | 82.0 | 1148 | 0.4421 | |
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| 0.2178 | 83.0 | 1162 | 0.4219 | |
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| 0.2178 | 84.0 | 1176 | 0.4328 | |
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| 0.2178 | 85.0 | 1190 | 0.4168 | |
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| 0.2178 | 86.0 | 1204 | 0.4724 | |
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| 0.2178 | 87.0 | 1218 | 0.4334 | |
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| 0.2178 | 88.0 | 1232 | 0.4430 | |
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| 0.2178 | 89.0 | 1246 | 0.4263 | |
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| 0.2178 | 90.0 | 1260 | 0.4126 | |
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| 0.2178 | 91.0 | 1274 | 0.4021 | |
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| 0.2178 | 92.0 | 1288 | 0.4027 | |
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| 0.2178 | 93.0 | 1302 | 0.4110 | |
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| 0.2178 | 94.0 | 1316 | 0.4199 | |
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| 0.2178 | 95.0 | 1330 | 0.4182 | |
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| 0.2178 | 96.0 | 1344 | 0.4171 | |
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| 0.2178 | 97.0 | 1358 | 0.4198 | |
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| 0.2178 | 98.0 | 1372 | 0.4200 | |
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| 0.2178 | 99.0 | 1386 | 0.4157 | |
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| 0.2178 | 100.0 | 1400 | 0.4148 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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