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NL-RX-Synth-t5-small-finetuned-en-to-regex
rymaju/NL-RX-Synth-t5-small-finetuned-en-to-regex
NL-RX-Synth-t5-small-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 5, 2022
- SHA
- 1a818b3b
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-small-finetuned-en-to-regex
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0131
- Semantic-accuracy: 0.36
- Gen Len: 18.24
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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Semantic-accuracy | Gen Len |
|---|---|---|---|---|---|
| 0.2382 | 1.0 | 563 | 0.0431 | 0.322 | 18.224 |
| 0.0477 | 2.0 | 1126 | 0.0229 | 0.356 | 18.236 |
| 0.0305 | 3.0 | 1689 | 0.0259 | 0.34 | 18.266 |
| 0.0231 | 4.0 | 2252 | 0.0204 | 0.35 | 18.238 |
| 0.0197 | 5.0 | 2815 | 0.0162 | 0.352 | 18.232 |
| 0.02 | 6.0 | 3378 | 0.0162 | 0.354 | 18.238 |
| 0.0172 | 7.0 | 3941 | 0.0147 | 0.356 | 18.24 |
| 0.0145 | 8.0 | 4504 | 0.0259 | 0.34 | 18.246 |
| 0.0133 | 9.0 | 5067 | 0.0129 | 0.358 | 18.238 |
| 0.0131 | 10.0 | 5630 | 0.0121 | 0.366 | 18.242 |
| 0.0122 | 11.0 | 6193 | 0.0128 | 0.354 | 18.242 |
| 0.0123 | 12.0 | 6756 | 0.0129 | 0.356 | 18.222 |
| 0.0113 | 13.0 | 7319 | 0.0131 | 0.362 | 18.232 |
| 0.0095 | 14.0 | 7882 | 0.0124 | 0.358 | 18.238 |
| 0.0102 | 15.0 | 8445 | 0.0127 | 0.362 | 18.244 |
| 0.0089 | 16.0 | 9008 | 0.0126 | 0.358 | 18.242 |
| 0.0086 | 17.0 | 9571 | 0.0133 | 0.358 | 18.242 |
| 0.0084 | 17.76 | 10000 | 0.0131 | 0.36 | 18.24 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 5, 2022
- Updated
- Dec 5, 2022