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PreDA-large

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t5
text2text-generation
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text-generation-inference
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lorenzoscottb/PreDA-t5

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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google-t5/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: PreDA_t5-large
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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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+ # PreDA_t5-large
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+
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+ This model is a fine-tuned version of [google-t5/t5-large](https://huggingface.co/google-t5/t5-large) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6073
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+ - Rouge1: 0.6587
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+ - Rouge2: 0.4979
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+ - Rougel: 0.6269
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+ - Rougelsum: 0.6270
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+
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+ ## Model description
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+
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+ More information needed than this
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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: linear
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+ - num_epochs: 20
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+ - label_smoothing_factor: 0.1
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 1.9478 | 1.0 | 539 | 1.9524 | 0.3298 | 0.1797 | 0.3121 | 0.3113 |
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+ | 1.9141 | 2.0 | 1078 | 1.9039 | 0.3665 | 0.1942 | 0.3495 | 0.3489 |
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+ | 1.914 | 3.0 | 1617 | 1.8993 | 0.4076 | 0.2223 | 0.3873 | 0.3870 |
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+ | 1.9264 | 4.0 | 2156 | 1.8725 | 0.3454 | 0.1843 | 0.3306 | 0.3302 |
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+ | 1.9018 | 5.0 | 2695 | 1.8669 | 0.3494 | 0.1814 | 0.3345 | 0.3347 |
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+ | 1.889 | 6.0 | 3234 | 1.8872 | 0.3387 | 0.1609 | 0.3211 | 0.3208 |
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+ | 1.8511 | 7.0 | 3773 | 1.8412 | 0.4200 | 0.2403 | 0.4065 | 0.4065 |
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+ | 1.8756 | 8.0 | 4312 | 1.8191 | 0.4735 | 0.2705 | 0.4467 | 0.4469 |
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+ | 1.8483 | 9.0 | 4851 | 1.7966 | 0.4915 | 0.2996 | 0.4662 | 0.4665 |
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+ | 1.8182 | 10.0 | 5390 | 1.7787 | 0.5071 | 0.3169 | 0.4857 | 0.4860 |
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+ | 1.7715 | 11.0 | 5929 | 1.7709 | 0.5017 | 0.3182 | 0.4767 | 0.4767 |
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+ | 1.7955 | 12.0 | 6468 | 1.7557 | 0.4772 | 0.3015 | 0.4544 | 0.4549 |
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+ | 1.7391 | 13.0 | 7007 | 1.7279 | 0.5644 | 0.3693 | 0.5270 | 0.5281 |
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+ | 1.7013 | 14.0 | 7546 | 1.7054 | 0.5484 | 0.3694 | 0.5222 | 0.5221 |
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+ | 1.7364 | 15.0 | 8085 | 1.6900 | 0.5607 | 0.3778 | 0.5349 | 0.5350 |
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+ | 1.6592 | 16.0 | 8624 | 1.6643 | 0.6010 | 0.4191 | 0.5691 | 0.5688 |
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+ | 1.645 | 17.0 | 9163 | 1.6448 | 0.6160 | 0.4440 | 0.5854 | 0.5863 |
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+ | 1.6245 | 18.0 | 9702 | 1.6264 | 0.6301 | 0.4640 | 0.6015 | 0.6018 |
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+ | 1.616 | 19.0 | 10241 | 1.6145 | 0.6578 | 0.4933 | 0.6253 | 0.6251 |
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+ | 1.5914 | 20.0 | 10780 | 1.6073 | 0.6587 | 0.4979 | 0.6269 | 0.6270 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 3.0.1
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+ - Tokenizers 0.19.1