|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: mymodel-generation |
|
|
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. --> |
|
|
|
|
|
# mymodel-generation |
|
|
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4959 |
|
|
- Rouge1: 15.814 |
|
|
- Rouge2: 6.0889 |
|
|
- Rougel: 13.524 |
|
|
- Rougelsum: 13.6797 |
|
|
- Gen Len: 19.0 |
|
|
|
|
|
## 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: 2e-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: 10 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
|
|
| No log | 1.0 | 100 | 0.6815 | 14.8968 | 4.9117 | 12.5655 | 12.7826 | 19.0 | |
|
|
| No log | 2.0 | 200 | 0.6100 | 14.9404 | 4.9974 | 12.8103 | 13.0953 | 19.0 | |
|
|
| No log | 3.0 | 300 | 0.5827 | 14.991 | 5.2082 | 12.9564 | 13.1979 | 19.0 | |
|
|
| No log | 4.0 | 400 | 0.5568 | 14.9205 | 5.1634 | 12.6664 | 12.8388 | 19.0 | |
|
|
| 0.8938 | 5.0 | 500 | 0.5352 | 15.2597 | 5.6541 | 13.0388 | 13.1956 | 19.0 | |
|
|
| 0.8938 | 6.0 | 600 | 0.5212 | 15.4645 | 5.7723 | 13.2198 | 13.3698 | 19.0 | |
|
|
| 0.8938 | 7.0 | 700 | 0.5098 | 15.4663 | 5.8769 | 13.2799 | 13.403 | 19.0 | |
|
|
| 0.8938 | 8.0 | 800 | 0.5015 | 16.0013 | 6.2874 | 13.7037 | 13.8538 | 19.0 | |
|
|
| 0.8938 | 9.0 | 900 | 0.4957 | 15.8722 | 6.1918 | 13.6299 | 13.7783 | 19.0 | |
|
|
| 0.6764 | 10.0 | 1000 | 0.4959 | 15.814 | 6.0889 | 13.524 | 13.6797 | 19.0 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.30.2 |
|
|
- Pytorch 2.0.1+cu118 |
|
|
- Datasets 2.13.1 |
|
|
- Tokenizers 0.13.3 |
|
|
|
