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---
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license: apache-2.0
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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-extraction-cnndm_10000-all
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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-extraction-cnndm_10000-all
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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: 1.7044
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- Rouge1: 34.8618
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- Rouge2: 15.5978
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- Rougel: 29.7948
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- Rougelsum: 29.7581
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- Gen Len: 19.0
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 24
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- seed: 1799
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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| 2.1668 | 0.16 | 200 | 1.8280 | 33.7941 | 14.3114 | 28.7743 | 28.7968 | 19.0 |
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| 1.9736 | 0.32 | 400 | 1.7818 | 34.8351 | 15.5548 | 29.8974 | 29.8557 | 18.99 |
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| 1.904 | 0.48 | 600 | 1.7513 | 35.465 | 15.8566 | 30.7139 | 30.6596 | 18.986 |
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| 1.8938 | 0.64 | 800 | 1.7440 | 34.6193 | 15.5473 | 30.0661 | 30.0019 | 18.99 |
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| 1.8471 | 0.8 | 1000 | 1.7366 | 34.553 | 15.2214 | 29.8807 | 29.8419 | 18.99 |
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| 1.8621 | 0.96 | 1200 | 1.7486 | 34.9309 | 15.1932 | 29.8973 | 29.8774 | 18.99 |
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| 1.8082 | 1.12 | 1400 | 1.7311 | 35.3395 | 16.0976 | 30.2748 | 30.293 | 18.99 |
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| 1.7448 | 1.28 | 1600 | 1.7155 | 35.1387 | 15.7462 | 29.924 | 29.9287 | 18.99 |
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| 1.7655 | 1.44 | 1800 | 1.7239 | 35.3603 | 15.6355 | 30.3944 | 30.3766 | 19.0 |
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| 1.7283 | 1.6 | 2000 | 1.7132 | 34.7368 | 15.4073 | 29.9027 | 29.8971 | 19.0 |
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| 1.7463 | 1.76 | 2200 | 1.7171 | 35.0545 | 15.726 | 30.0364 | 30.0056 | 19.0 |
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| 1.7462 | 1.92 | 2400 | 1.7044 | 34.8618 | 15.5978 | 29.7948 | 29.7581 | 19.0 |
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| 1.719 | 2.08 | 2600 | 1.7285 | 34.9598 | 15.5237 | 29.5593 | 29.5803 | 19.0 |
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| 1.6828 | 2.24 | 2800 | 1.7179 | 35.0944 | 15.7333 | 29.8381 | 29.7784 | 19.0 |
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| 1.7 | 2.4 | 3000 | 1.7047 | 35.1766 | 15.7758 | 29.818 | 29.7859 | 19.0 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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