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t5-small-med-term-mlm
gayanin/t5-small-med-term-mlm
t5-small-med-term-mlm 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 8, 2022
- Updated
- Mar 8, 2022
- SHA
- 3e6a9457
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-med-term-mlm
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4736
- Rouge2 Precision: 0.7731
- Rouge2 Recall: 0.5541
- Rouge2 Fmeasure: 0.6251
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.6498 | 1.0 | 15827 | 0.5480 | 0.7629 | 0.5457 | 0.6161 |
| 0.5674 | 2.0 | 31654 | 0.4989 | 0.7697 | 0.551 | 0.622 |
| 0.5631 | 3.0 | 47481 | 0.4795 | 0.7726 | 0.5541 | 0.625 |
| 0.534 | 4.0 | 63308 | 0.4736 | 0.7731 | 0.5541 | 0.6251 |
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 8, 2022
- Updated
- Mar 8, 2022