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t5-small-mlm-paraphrasing
gayanin/t5-small-mlm-paraphrasing
t5-small-mlm-paraphrasing is a machine learning model from gayanin. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Mar 7, 2022
- Updated
- Mar 7, 2022
- SHA
- f65b3eec
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
t5-small-mlm-paraphrasing
This model is a fine-tuned version of gayanin/t5-small-mlm-pubmed on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4243
- Rouge2 Precision: 0.8281
- Rouge2 Recall: 0.6508
- Rouge2 Fmeasure: 0.7125
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.6445 | 0.75 | 500 | 0.5049 | 0.821 | 0.6477 | 0.7078 |
| 0.5227 | 1.51 | 1000 | 0.4748 | 0.8243 | 0.6492 | 0.7099 |
| 0.5126 | 2.26 | 1500 | 0.4594 | 0.8254 | 0.6506 | 0.7111 |
| 0.4858 | 3.02 | 2000 | 0.4492 | 0.8266 | 0.651 | 0.712 |
| 0.4669 | 3.77 | 2500 | 0.4421 | 0.8268 | 0.6508 | 0.7118 |
| 0.4684 | 4.52 | 3000 | 0.4374 | 0.8272 | 0.6513 | 0.7124 |
| 0.463 | 5.28 | 3500 | 0.4342 | 0.8274 | 0.6508 | 0.712 |
| 0.4558 | 6.03 | 4000 | 0.4301 | 0.8278 | 0.6508 | 0.7123 |
| 0.4553 | 6.79 | 4500 | 0.4283 | 0.8279 | 0.6507 | 0.7122 |
| 0.443 | 7.54 | 5000 | 0.4259 | 0.8281 | 0.6511 | 0.7125 |
| 0.441 | 8.3 | 5500 | 0.4263 | 0.828 | 0.6503 | 0.7121 |
| 0.444 | 9.05 | 6000 | 0.4244 | 0.8281 | 0.6507 | 0.7125 |
| 0.4392 | 9.8 | 6500 | 0.4243 | 0.8281 | 0.6508 | 0.7125 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 7, 2022
- Updated
- Mar 7, 2022