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README.md
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---
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license: cc-by-4.0
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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-squad
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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-squad
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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: 5.0220
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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: 0.0001
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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: 30
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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 | 74 | 1.7148 |
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| No log | 2.0 | 148 | 1.6994 |
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| No log | 3.0 | 222 | 1.7922 |
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| No log | 4.0 | 296 | 1.9947 |
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| No log | 5.0 | 370 | 2.0753 |
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| No log | 6.0 | 444 | 2.2096 |
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| 0.9547 | 7.0 | 518 | 2.3070 |
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| 0.9547 | 8.0 | 592 | 2.6947 |
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| 0.9547 | 9.0 | 666 | 2.7169 |
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| 0.9547 | 10.0 | 740 | 2.8503 |
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| 0.9547 | 11.0 | 814 | 3.1990 |
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| 0.9547 | 12.0 | 888 | 3.4931 |
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| 0.9547 | 13.0 | 962 | 3.6575 |
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| 0.3191 | 14.0 | 1036 | 3.1863 |
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| 0.3191 | 15.0 | 1110 | 3.7922 |
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| 0.3191 | 16.0 | 1184 | 3.6336 |
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| 0.3191 | 17.0 | 1258 | 4.1156 |
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| 0.3191 | 18.0 | 1332 | 4.1353 |
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| 0.3191 | 19.0 | 1406 | 3.9888 |
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| 0.3191 | 20.0 | 1480 | 4.4290 |
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| 0.1904 | 21.0 | 1554 | 4.0473 |
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| 0.1904 | 22.0 | 1628 | 4.5048 |
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| 0.1904 | 23.0 | 1702 | 4.4026 |
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| 0.1904 | 24.0 | 1776 | 4.2864 |
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| 0.1904 | 25.0 | 1850 | 4.3941 |
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| 0.1904 | 26.0 | 1924 | 4.4921 |
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| 0.1904 | 27.0 | 1998 | 4.9139 |
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| 0.1342 | 28.0 | 2072 | 4.8914 |
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| 0.1342 | 29.0 | 2146 | 5.0148 |
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| 0.1342 | 30.0 | 2220 | 5.0220 |
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### Framework versions
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- Transformers 4.11.0
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- Pytorch 1.9.0+cu102
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- Datasets 1.12.1
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- Tokenizers 0.10.3
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