File size: 2,471 Bytes
376fc99 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | ---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: EN_mt5-base_10_wikiSQL
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. -->
# EN_mt5-base_10_wikiSQL
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0849
- Rouge2 Precision: 0.864
- Rouge2 Recall: 0.787
- Rouge2 Fmeasure: 0.8178
## 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: 21
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.1677 | 1.0 | 3085 | 0.1224 | 0.8269 | 0.7506 | 0.7803 |
| 0.1287 | 2.0 | 6170 | 0.1028 | 0.8458 | 0.7673 | 0.7988 |
| 0.1086 | 3.0 | 9255 | 0.0959 | 0.8511 | 0.7727 | 0.8042 |
| 0.0965 | 4.0 | 12340 | 0.0900 | 0.8543 | 0.777 | 0.808 |
| 0.089 | 5.0 | 15425 | 0.0883 | 0.8575 | 0.7802 | 0.8111 |
| 0.0809 | 6.0 | 18510 | 0.0866 | 0.8606 | 0.7834 | 0.8143 |
| 0.0771 | 7.0 | 21595 | 0.0860 | 0.8625 | 0.7851 | 0.8161 |
| 0.0745 | 8.0 | 24680 | 0.0855 | 0.8633 | 0.7862 | 0.8171 |
| 0.0715 | 9.0 | 27765 | 0.0848 | 0.8641 | 0.7869 | 0.8178 |
| 0.0702 | 10.0 | 30850 | 0.0849 | 0.864 | 0.787 | 0.8178 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
|