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t5-small-ruleviewer
Tgratzi/t5-small-ruleviewer
t5-small-ruleviewer is a machine learning model from Tgratzi. 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
- Feb 2, 2024
- Updated
- Feb 25, 2024
- SHA
- c456032b
Base models
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-ruleviewer
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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: 0.001
- 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
- lr_scheduler_warmup_steps: 200
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8028 | 4.88 | 200 | 0.0162 |
| 0.0196 | 9.76 | 400 | 0.0010 |
| 0.0071 | 14.63 | 600 | 0.0002 |
| 0.0033 | 19.51 | 800 | 0.0001 |
| 0.0019 | 24.39 | 1000 | 0.0000 |
| 0.0014 | 29.27 | 1200 | 0.0000 |
| 0.0011 | 34.15 | 1400 | 0.0000 |
| 0.0008 | 39.02 | 1600 | 0.0000 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Feb 2, 2024
- Updated
- Feb 25, 2024