|
---
|
|
library_name: transformers
|
|
license: apache-2.0
|
|
base_model: google/mt5-base
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- wikisql
|
|
model-index:
|
|
- name: mt5_base_EN_sch_wiki
|
|
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. -->
|
|
|
|
# mt5_base_EN_sch_wiki
|
|
|
|
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: nan
|
|
- Rouge2 Precision: 0.0165
|
|
- Rouge2 Recall: 0.0087
|
|
- Rouge2 Fmeasure: 0.0111
|
|
|
|
## 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: 14
|
|
- eval_batch_size: 16
|
|
- seed: 42
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
|
|
- lr_scheduler_type: linear
|
|
- num_epochs: 15
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
|
|
| 0.0 | 1.0 | 4627 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 2.0 | 9254 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 3.0 | 13881 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 4.0 | 18508 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 5.0 | 23135 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 6.0 | 27762 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 7.0 | 32389 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 8.0 | 37016 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 9.0 | 41643 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 10.0 | 46270 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 11.0 | 50897 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 12.0 | 55524 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 13.0 | 60151 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 14.0 | 64778 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
| 0.0 | 15.0 | 69405 | nan | 0.0165 | 0.0087 | 0.0111 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.46.2
|
|
- Pytorch 2.2.2
|
|
- Datasets 2.16.1
|
|
- Tokenizers 0.20.3
|
|
|