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--- |
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license: cc-by-4.0 |
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base_model: deepset/roberta-base-squad2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: roberta-base-squad2-finetuned-newqa1 |
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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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# roberta-base-squad2-finetuned-newqa1 |
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This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.3201 |
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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: 5e-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: 20 |
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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 | 66 | 2.2730 | |
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| No log | 2.0 | 132 | 1.9853 | |
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| No log | 3.0 | 198 | 2.0627 | |
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| No log | 4.0 | 264 | 2.3190 | |
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| No log | 5.0 | 330 | 2.5382 | |
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| No log | 6.0 | 396 | 3.0129 | |
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| No log | 7.0 | 462 | 3.0762 | |
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| 1.127 | 8.0 | 528 | 3.3226 | |
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| 1.127 | 9.0 | 594 | 3.4531 | |
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| 1.127 | 10.0 | 660 | 3.9486 | |
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| 1.127 | 11.0 | 726 | 3.7776 | |
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| 1.127 | 12.0 | 792 | 3.5990 | |
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| 1.127 | 13.0 | 858 | 3.7593 | |
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| 1.127 | 14.0 | 924 | 4.0871 | |
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| 1.127 | 15.0 | 990 | 4.0839 | |
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| 0.1163 | 16.0 | 1056 | 4.2244 | |
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| 0.1163 | 17.0 | 1122 | 4.2595 | |
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| 0.1163 | 18.0 | 1188 | 4.3196 | |
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| 0.1163 | 19.0 | 1254 | 4.3051 | |
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| 0.1163 | 20.0 | 1320 | 4.3201 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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