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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- squad_modified_for_t5_qg
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model-index:
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- name: t5-end2end-questions-generation
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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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# t5-end2end-questions-generation
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This model is a fine-tuned version of [digit82/kolang-t5-base](https://huggingface.co/digit82/kolang-t5-base) on the squad_modified_for_t5_qg dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1449
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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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: 7
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 3.6685 | 0.66 | 100 | 2.4355 |
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| 2.3957 | 1.32 | 200 | 2.2428 |
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| 2.1795 | 1.98 | 300 | 2.1664 |
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| 1.9408 | 2.65 | 400 | 2.1467 |
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| 1.8333 | 3.31 | 500 | 2.1470 |
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| 1.7319 | 3.97 | 600 | 2.1194 |
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| 1.6095 | 4.63 | 700 | 2.1348 |
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| 1.5662 | 5.3 | 800 | 2.1433 |
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| 1.5038 | 5.96 | 900 | 2.1319 |
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| 1.45 | 6.62 | 1000 | 2.1449 |
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### Framework versions
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- Transformers 4.21.2
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- Pytorch 1.12.1+cu113
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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