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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/flan-t5-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ - f1
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+ - recall
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+ - precision
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+ model-index:
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+ - name: KGAQ-2
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+ results: []
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+ ---
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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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+
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+ # KGAQ-2
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+
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+ This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.6712
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+ - Rouge1: 9.9002
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+ - Rouge2: 0.817
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+ - Rougel: 9.31
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+ - Rougelsum: 9.8757
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+ - Gen Len: 4.0
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+ - F1: 0.0005
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+ - Recall: 0.0008
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+ - Precision: 0.0003
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: cosine_with_restarts
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | F1 | Recall | Precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|:------:|:------:|:---------:|
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+ | 3.5701 | 1.0 | 598 | 3.3914 | 14.1052 | 1.2078 | 13.0257 | 14.1332 | 3.0 | 0.0 | 0.0 | 0.0 |
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+ | 3.0379 | 2.0 | 1196 | 2.7468 | 12.4379 | 1.0435 | 11.3645 | 12.4814 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 2.2773 | 3.0 | 1794 | 2.4962 | 25.6591 | 2.6653 | 16.5422 | 25.687 | 6.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.8845 | 4.0 | 2392 | 2.4370 | 8.8131 | 0.2887 | 8.1866 | 8.8014 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 1.7721 | 5.0 | 2990 | 2.5342 | 8.2864 | 0.5105 | 7.6569 | 8.2655 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 2.1007 | 6.0 | 3588 | 2.5028 | 27.8343 | 3.8693 | 19.0586 | 27.8325 | 6.4795 | 0.0022 | 0.0036 | 0.0015 |
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+ | 2.0255 | 7.0 | 4186 | 2.5544 | 8.2864 | 0.5105 | 7.6569 | 8.2655 | 3.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 1.9177 | 8.0 | 4784 | 2.5356 | 22.6347 | 3.1887 | 14.2667 | 22.6751 | 7.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 1.7165 | 9.0 | 5382 | 2.5492 | 9.9002 | 0.817 | 9.31 | 9.8757 | 4.0 | 0.0005 | 0.0008 | 0.0003 |
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+ | 1.645 | 10.0 | 5980 | 2.6712 | 9.9002 | 0.817 | 9.31 | 9.8757 | 4.0 | 0.0005 | 0.0008 | 0.0003 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "transformers_version": "4.43.3"
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+ }
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