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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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model-index: |
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- name: flan-t5-large_question_answering_finetuining |
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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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# flan-t5-large_question_answering_finetuining |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6768 |
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- Rouge1: 16.22 |
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- Rouge2: 9.65 |
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- Rougel: 15.62 |
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- Rougelsum: 15.75 |
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- R: 13.82 |
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- Gen Len: 30.3456 |
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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: 0.0003 |
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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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- 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | R | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-----:|:-------:| |
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| 10.4307 | 1.0 | 79 | 0.5836 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | |
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| 0.4454 | 2.0 | 158 | 0.4834 | 4.07 | 0.61 | 4.18 | 4.15 | 2.95 | 13.7574 | |
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| 0.3152 | 3.0 | 237 | 0.4520 | 7.89 | 2.42 | 7.49 | 7.53 | 5.93 | 27.9044 | |
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| 0.2321 | 4.0 | 316 | 0.4634 | 7.5 | 3.24 | 7.41 | 7.39 | 6.05 | 20.0588 | |
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| 0.1775 | 5.0 | 395 | 0.4656 | 12.1 | 5.52 | 11.98 | 11.81 | 9.86 | 21.1176 | |
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| 0.1299 | 6.0 | 474 | 0.4958 | 15.28 | 8.79 | 14.71 | 14.68 | 12.92 | 22.9044 | |
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| 0.096 | 7.0 | 553 | 0.5332 | 15.42 | 9.23 | 14.84 | 14.94 | 13.15 | 28.3382 | |
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| 0.0685 | 8.0 | 632 | 0.6132 | 15.45 | 9.76 | 15.07 | 14.99 | 13.42 | 26.4559 | |
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| 0.0542 | 9.0 | 711 | 0.6218 | 17.08 | 11.34 | 16.54 | 16.67 | 14.98 | 28.2353 | |
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| 0.0442 | 10.0 | 790 | 0.6768 | 16.22 | 9.65 | 15.62 | 15.75 | 13.82 | 30.3456 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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