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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-large-cased-sigir-support-no-label-40 |
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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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# bert-large-cased-sigir-support-no-label-40 |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1107 |
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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: 4e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 30 |
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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: 40.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.7638 | 1.0 | 246 | 2.2805 | |
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| 2.1924 | 2.0 | 492 | 1.9602 | |
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| 1.8921 | 3.0 | 738 | 1.7992 | |
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| 1.7412 | 4.0 | 984 | 1.7229 | |
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| 1.6311 | 5.0 | 1230 | 1.6165 | |
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| 1.5421 | 6.0 | 1476 | 1.5400 | |
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| 1.4619 | 7.0 | 1722 | 1.5001 | |
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| 1.3846 | 8.0 | 1968 | 1.4381 | |
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| 1.3414 | 9.0 | 2214 | 1.4285 | |
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| 1.2894 | 10.0 | 2460 | 1.4108 | |
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| 1.2467 | 11.0 | 2706 | 1.3460 | |
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| 1.1992 | 12.0 | 2952 | 1.3434 | |
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| 1.1612 | 13.0 | 3198 | 1.2951 | |
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| 1.1266 | 14.0 | 3444 | 1.2518 | |
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| 1.0933 | 15.0 | 3690 | 1.2825 | |
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| 1.0625 | 16.0 | 3936 | 1.2523 | |
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| 1.0386 | 17.0 | 4182 | 1.2251 | |
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| 1.0066 | 18.0 | 4428 | 1.2339 | |
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| 0.9755 | 19.0 | 4674 | 1.1887 | |
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| 0.9656 | 20.0 | 4920 | 1.2288 | |
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| 0.9517 | 21.0 | 5166 | 1.1391 | |
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| 0.9207 | 22.0 | 5412 | 1.1718 | |
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| 0.8964 | 23.0 | 5658 | 1.1850 | |
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| 0.8891 | 24.0 | 5904 | 1.1306 | |
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| 0.8564 | 25.0 | 6150 | 1.1956 | |
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| 0.851 | 26.0 | 6396 | 1.1263 | |
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| 0.8331 | 27.0 | 6642 | 1.1060 | |
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| 0.8143 | 28.0 | 6888 | 1.0689 | |
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| 0.7972 | 29.0 | 7134 | 1.0772 | |
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| 0.7857 | 30.0 | 7380 | 1.1103 | |
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| 0.7687 | 31.0 | 7626 | 1.1635 | |
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| 0.7653 | 32.0 | 7872 | 1.0736 | |
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| 0.777 | 33.0 | 8118 | 1.1103 | |
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| 0.741 | 34.0 | 8364 | 1.0830 | |
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| 0.7408 | 35.0 | 8610 | 1.0809 | |
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| 0.736 | 36.0 | 8856 | 1.0894 | |
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| 0.7362 | 37.0 | 9102 | 1.0691 | |
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| 0.727 | 38.0 | 9348 | 1.0519 | |
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| 0.715 | 39.0 | 9594 | 1.0919 | |
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| 0.7286 | 40.0 | 9840 | 1.1107 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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