|
--- |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: ALL_manual_mt5-base_15_spider_no_sch_15_wikiSQL_no_sch |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ALL_manual_mt5-base_15_spider_no_sch_15_wikiSQL_no_sch |
|
|
|
This model was trained from scratch on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0276 |
|
- Rouge2 Precision: 0.8193 |
|
- Rouge2 Recall: 0.5491 |
|
- Rouge2 Fmeasure: 0.6245 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 15 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
|
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
|
| 0.3496 | 1.0 | 1293 | 0.2017 | 0.4711 | 0.3028 | 0.3466 | |
|
| 0.2041 | 2.0 | 2586 | 0.1328 | 0.5656 | 0.3798 | 0.4292 | |
|
| 0.1637 | 3.0 | 3879 | 0.0987 | 0.6111 | 0.4058 | 0.4602 | |
|
| 0.1294 | 4.0 | 5172 | 0.0791 | 0.6546 | 0.4366 | 0.4953 | |
|
| 0.1124 | 5.0 | 6465 | 0.0658 | 0.6947 | 0.4679 | 0.53 | |
|
| 0.0968 | 6.0 | 7758 | 0.0563 | 0.7264 | 0.4901 | 0.5555 | |
|
| 0.084 | 7.0 | 9051 | 0.0480 | 0.7492 | 0.5063 | 0.5737 | |
|
| 0.0782 | 8.0 | 10344 | 0.0428 | 0.7561 | 0.5075 | 0.5768 | |
|
| 0.0701 | 9.0 | 11637 | 0.0379 | 0.7758 | 0.522 | 0.5928 | |
|
| 0.0669 | 10.0 | 12930 | 0.0350 | 0.7904 | 0.5316 | 0.6039 | |
|
| 0.0623 | 11.0 | 14223 | 0.0318 | 0.8102 | 0.5432 | 0.6175 | |
|
| 0.059 | 12.0 | 15516 | 0.0299 | 0.8047 | 0.5413 | 0.615 | |
|
| 0.0562 | 13.0 | 16809 | 0.0286 | 0.8149 | 0.546 | 0.6214 | |
|
| 0.0548 | 14.0 | 18102 | 0.0279 | 0.8167 | 0.5478 | 0.6229 | |
|
| 0.0538 | 15.0 | 19395 | 0.0276 | 0.8193 | 0.5491 | 0.6245 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.0 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|