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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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+ model-index:
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+ - name: t5-small-paraphrasing-mlm
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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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+ # t5-small-paraphrasing-mlm
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+
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+ This model is a fine-tuned version of [gayanin/t5-small-paraphrase-pubmed](https://huggingface.co/gayanin/t5-small-paraphrase-pubmed) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7030
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+ - Rouge2 Precision: 0.6576
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+ - Rouge2 Recall: 0.4712
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+ - Rouge2 Fmeasure: 0.532
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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: 2e-05
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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: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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+ |:-------------:|:-----:|:------:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | 0.9215 | 1.0 | 13833 | 0.8050 | 0.6352 | 0.454 | 0.5131 |
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+ | 0.855 | 2.0 | 27666 | 0.7679 | 0.6411 | 0.4589 | 0.5184 |
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+ | 0.8387 | 3.0 | 41499 | 0.7464 | 0.6464 | 0.4626 | 0.5226 |
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+ | 0.8267 | 4.0 | 55332 | 0.7315 | 0.6513 | 0.4671 | 0.5273 |
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+ | 0.7879 | 5.0 | 69165 | 0.7217 | 0.6534 | 0.4687 | 0.529 |
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+ | 0.7738 | 6.0 | 82998 | 0.7142 | 0.6548 | 0.4688 | 0.5295 |
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+ | 0.7793 | 7.0 | 96831 | 0.7094 | 0.6553 | 0.4694 | 0.53 |
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+ | 0.7654 | 8.0 | 110664 | 0.7056 | 0.6573 | 0.4704 | 0.5313 |
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+ | 0.7675 | 9.0 | 124497 | 0.7036 | 0.6577 | 0.4712 | 0.532 |
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+ | 0.7662 | 10.0 | 138330 | 0.7030 | 0.6576 | 0.4712 | 0.532 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.18.4
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+ - Tokenizers 0.11.6