KB13-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: 0.4785
- Semantic accuracy: 0.3902
- Syntactic accuracy: 0.3171
- Gen Len: 15.2927
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 | 2.13 | 100 | 0.7159 | 0.122 | 0.0976 | 15.2439 |
| No log | 4.26 | 200 | 0.4649 | 0.2683 | 0.2195 | 15.0488 |
| No log | 6.38 | 300 | 0.3749 | 0.4146 | 0.3415 | 15.3659 |
| No log | 8.51 | 400 | 0.4155 | 0.3902 | 0.2927 | 15.0976 |
| 0.5191 | 10.64 | 500 | 0.4148 | 0.3902 | 0.2927 | 15.7561 |
| 0.5191 | 12.77 | 600 | 0.4010 | 0.439 | 0.3415 | 15.3902 |
| 0.5191 | 14.89 | 700 | 0.4429 | 0.3902 | 0.3171 | 15.3659 |
| 0.5191 | 17.02 | 800 | 0.4607 | 0.3902 | 0.3415 | 15.561 |
| 0.5191 | 19.15 | 900 | 0.4629 | 0.3902 | 0.3171 | 15.122 |
| 0.0518 | 21.28 | 1000 | 0.4785 | 0.3902 | 0.3171 | 15.2927 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2