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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: KGQA-1 |
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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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# KGQA-1 |
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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: 2.0784 |
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- Rouge1: 72.8963 |
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- Rouge2: 60.8929 |
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- Rougel: 69.6657 |
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- Rougelsum: 72.9329 |
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- Gen Len: 4.8819 |
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- F1: 0.7593 |
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- Recall: 0.7681 |
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- Precision: 0.7508 |
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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: 0.001 |
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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: 8 |
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### Training results |
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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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| 2.8587 | 1.0 | 598 | 2.2931 | 49.5203 | 26.8249 | 43.3252 | 49.5005 | 4.6943 | 0.5633 | 0.5546 | 0.5723 | |
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| 1.7685 | 2.0 | 1196 | 1.6857 | 52.6345 | 31.7615 | 46.5617 | 52.5831 | 4.7965 | 0.619 | 0.6295 | 0.6088 | |
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| 0.8979 | 3.0 | 1794 | 1.3095 | 65.3839 | 49.1969 | 60.9907 | 65.2835 | 4.8928 | 0.6898 | 0.6806 | 0.6992 | |
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| 0.4881 | 4.0 | 2392 | 1.4524 | 68.0576 | 53.7819 | 64.3964 | 67.9986 | 4.835 | 0.7239 | 0.7106 | 0.7378 | |
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| 1.2094 | 5.0 | 2990 | 3.2070 | 18.934 | 4.1916 | 14.7003 | 18.9198 | 6.0159 | 0.0005 | 0.001 | 0.0003 | |
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| 0.7018 | 6.0 | 3588 | 1.3772 | 68.1255 | 54.2242 | 64.3339 | 68.1513 | 4.7588 | 0.7125 | 0.69 | 0.7366 | |
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| 0.3275 | 7.0 | 4186 | 1.5585 | 72.2516 | 60.2665 | 68.9117 | 72.2482 | 4.9246 | 0.7643 | 0.7827 | 0.7468 | |
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| 0.112 | 8.0 | 4784 | 2.0784 | 72.8963 | 60.8929 | 69.6657 | 72.9329 | 4.8819 | 0.7593 | 0.7681 | 0.7508 | |
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### Framework versions |
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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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