|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: EN_mt5-base_15_spider |
|
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_15_spider |
|
|
|
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4677 |
|
- Rouge2 Precision: 0.5384 |
|
- Rouge2 Recall: 0.3712 |
|
- Rouge2 Fmeasure: 0.413 |
|
|
|
## 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: 16 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
|
| No log | 1.0 | 438 | 1.7721 | 0.0 | 0.0 | 0.0 | |
|
| 10.9203 | 2.0 | 876 | 1.5463 | 0.0048 | 0.0008 | 0.0015 | |
|
| 1.7683 | 3.0 | 1314 | 1.3623 | 0.0164 | 0.0008 | 0.0014 | |
|
| 1.6091 | 4.0 | 1752 | 1.0649 | 0.0036 | 0.0012 | 0.0014 | |
|
| 1.2253 | 5.0 | 2190 | 0.3614 | 0.2985 | 0.1906 | 0.2088 | |
|
| 0.3973 | 6.0 | 2628 | 0.3133 | 0.4588 | 0.2914 | 0.3317 | |
|
| 0.2032 | 7.0 | 3066 | 0.3007 | 0.5065 | 0.3375 | 0.3799 | |
|
| 0.1597 | 8.0 | 3504 | 0.3109 | 0.5212 | 0.3579 | 0.3988 | |
|
| 0.1597 | 9.0 | 3942 | 0.3431 | 0.5194 | 0.3529 | 0.3931 | |
|
| 0.1385 | 10.0 | 4380 | 0.4681 | 0.5315 | 0.3636 | 0.4051 | |
|
| 0.1285 | 11.0 | 4818 | 0.5505 | 0.5331 | 0.3666 | 0.4074 | |
|
| 0.1228 | 12.0 | 5256 | 0.5351 | 0.5331 | 0.3645 | 0.4063 | |
|
| 0.1092 | 13.0 | 5694 | 0.4808 | 0.5355 | 0.3697 | 0.4102 | |
|
| 0.1078 | 14.0 | 6132 | 0.4519 | 0.5407 | 0.3727 | 0.4144 | |
|
| 0.1034 | 15.0 | 6570 | 0.4677 | 0.5384 | 0.3712 | 0.413 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.7.dev0 |
|
- Tokenizers 0.13.3 |
|
|
