|
--- |
|
license: cc-by-sa-4.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: bart-base-japanese-tobyoki-pairwise-wo_space |
|
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. --> |
|
|
|
# bart-base-japanese-tobyoki-pairwise-wo_space |
|
|
|
This model is a fine-tuned version of [ku-nlp/bart-base-japanese](https://huggingface.co/ku-nlp/bart-base-japanese) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.2694 |
|
- Rouge1: 18.7407 |
|
- Rouge2: 3.1211 |
|
- Rougel: 10.9379 |
|
- Rougelsum: 15.8203 |
|
- Gen Len: 95.0245 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:| |
|
| 0.7833 | 1.0 | 2025 | 2.5751 | 16.3343 | 1.2888 | 11.0128 | 15.2802 | 65.3776 | |
|
| 0.3308 | 2.0 | 4050 | 2.9423 | 17.9514 | 2.8091 | 10.9133 | 15.4068 | 91.6503 | |
|
| 0.2302 | 3.0 | 6075 | 3.0625 | 16.1453 | 3.0026 | 10.272 | 14.0716 | 77.1993 | |
|
| 0.1576 | 4.0 | 8100 | 3.2308 | 17.8409 | 2.9937 | 10.8765 | 15.6203 | 88.3986 | |
|
| 0.1055 | 5.0 | 10125 | 3.2694 | 18.7407 | 3.1211 | 10.9379 | 15.8203 | 95.0245 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|