|
--- |
|
license: apache-2.0 |
|
base_model: google/flan-t5-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: flant5action |
|
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. --> |
|
|
|
# flant5action |
|
|
|
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1428 |
|
- Rouge1: 56.0664 |
|
- Rouge2: 34.7343 |
|
- Rougel: 56.0394 |
|
- Rougelsum: 56.0313 |
|
- Gen Len: 18.9852 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 0.2525 | 1.0 | 674 | 0.2294 | 53.2181 | 29.8509 | 53.1635 | 53.1474 | 19.0 | |
|
| 0.2434 | 2.0 | 1348 | 0.2240 | 53.5453 | 30.1367 | 53.4479 | 53.44 | 18.9970 | |
|
| 0.2281 | 3.0 | 2022 | 0.2135 | 53.1901 | 30.3456 | 53.0849 | 53.0759 | 18.9970 | |
|
| 0.2221 | 4.0 | 2696 | 0.2056 | 52.0669 | 29.4321 | 51.9567 | 51.9512 | 18.9881 | |
|
| 0.2145 | 5.0 | 3370 | 0.2012 | 54.484 | 31.6451 | 54.4213 | 54.4144 | 18.9970 | |
|
| 0.2121 | 6.0 | 4044 | 0.1961 | 54.1219 | 31.2019 | 54.0701 | 54.0668 | 18.9970 | |
|
| 0.1979 | 7.0 | 4718 | 0.1901 | 54.9091 | 32.2416 | 54.8482 | 54.8318 | 18.9911 | |
|
| 0.2086 | 8.0 | 5392 | 0.1846 | 54.9615 | 32.4701 | 54.8836 | 54.8821 | 18.9970 | |
|
| 0.1985 | 9.0 | 6066 | 0.1795 | 55.2027 | 32.5792 | 55.1531 | 55.1431 | 18.9970 | |
|
| 0.2027 | 10.0 | 6740 | 0.1746 | 54.4079 | 32.2598 | 54.38 | 54.3697 | 18.9970 | |
|
| 0.1922 | 11.0 | 7414 | 0.1707 | 55.4814 | 33.2069 | 55.4428 | 55.4298 | 18.9970 | |
|
| 0.1806 | 12.0 | 8088 | 0.1660 | 55.7189 | 33.831 | 55.6796 | 55.6702 | 18.9970 | |
|
| 0.1834 | 13.0 | 8762 | 0.1623 | 55.6253 | 33.9516 | 55.5925 | 55.585 | 18.9941 | |
|
| 0.1795 | 14.0 | 9436 | 0.1596 | 55.6786 | 33.7589 | 55.6232 | 55.6183 | 18.9911 | |
|
| 0.1767 | 15.0 | 10110 | 0.1553 | 55.8132 | 34.1603 | 55.795 | 55.7873 | 18.9911 | |
|
| 0.1792 | 16.0 | 10784 | 0.1539 | 55.9694 | 34.4612 | 55.9454 | 55.9323 | 18.9792 | |
|
| 0.1785 | 17.0 | 11458 | 0.1521 | 56.2202 | 34.6224 | 56.1781 | 56.1706 | 18.9941 | |
|
| 0.1705 | 18.0 | 12132 | 0.1496 | 56.4102 | 34.7821 | 56.3911 | 56.3789 | 18.9911 | |
|
| 0.1668 | 19.0 | 12806 | 0.1478 | 56.1222 | 34.6804 | 56.0821 | 56.077 | 18.9881 | |
|
| 0.1729 | 20.0 | 13480 | 0.1459 | 56.1605 | 34.8596 | 56.1349 | 56.1221 | 18.9852 | |
|
| 0.1759 | 21.0 | 14154 | 0.1451 | 56.1232 | 34.8956 | 56.1054 | 56.0994 | 18.9852 | |
|
| 0.1713 | 22.0 | 14828 | 0.1439 | 55.9801 | 34.6435 | 55.9556 | 55.9482 | 18.9763 | |
|
| 0.1751 | 23.0 | 15502 | 0.1436 | 56.2088 | 34.8754 | 56.1771 | 56.1758 | 18.9852 | |
|
| 0.1626 | 24.0 | 16176 | 0.1431 | 56.0657 | 34.7302 | 56.04 | 56.0317 | 18.9852 | |
|
| 0.1696 | 25.0 | 16850 | 0.1428 | 56.0664 | 34.7343 | 56.0394 | 56.0313 | 18.9852 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.3 |
|
- Tokenizers 0.13.3 |
|
|
