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NL-RX-Synth-t5-base-finetuned-en-to-regex
rymaju/NL-RX-Synth-t5-base-finetuned-en-to-regex
NL-RX-Synth-t5-base-finetuned-en-to-regex is a machine learning model from rymaju. 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
- Dec 5, 2022
- Updated
- Dec 17, 2022
- SHA
- f953fa93
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. -->
NL-RX-Synth-t5-base-finetuned-en-to-regex
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0255
- Semantic accuracy: 0.336
- Syntactic accuracy: 0.286
- Gen Len: 18.316
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Semantic accuracy | Syntactic accuracy | Gen Len |
|---|---|---|---|---|---|---|
| No log | 0.18 | 100 | 0.2726 | 0.242 | 0.158 | 18.09 |
| No log | 0.36 | 200 | 0.1477 | 0.264 | 0.2 | 18.268 |
| No log | 0.53 | 300 | 0.1153 | 0.262 | 0.224 | 18.298 |
| No log | 0.71 | 400 | 0.0602 | 0.292 | 0.242 | 18.266 |
| 0.2992 | 0.89 | 500 | 0.0526 | 0.32 | 0.276 | 18.282 |
| 0.2992 | 1.07 | 600 | 0.0396 | 0.318 | 0.272 | 18.3 |
| 0.2992 | 1.24 | 700 | 0.0326 | 0.318 | 0.286 | 18.33 |
| 0.2992 | 1.42 | 800 | 0.0322 | 0.326 | 0.28 | 18.314 |
| 0.2992 | 1.6 | 900 | 0.0267 | 0.326 | 0.278 | 18.328 |
| 0.0383 | 1.78 | 1000 | 0.0255 | 0.336 | 0.286 | 18.316 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 5, 2022
- Updated
- Dec 17, 2022