|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- jsonl_dataset_sum.py |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: summarization_all |
|
results: |
|
- task: |
|
name: Summarization |
|
type: summarization |
|
dataset: |
|
name: jsonl_dataset_sum.py |
|
type: jsonl_dataset_sum.py |
|
config: 'null' |
|
split: None |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 21.9857 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# summarization_all |
|
|
|
This model is a fine-tuned version of [KETI-AIR/long-ke-t5-base](https://huggingface.co/KETI-AIR/long-ke-t5-base) on the jsonl_dataset_sum.py dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1442 |
|
- Rouge1: 21.9857 |
|
- Rouge2: 10.2876 |
|
- Rougel: 21.4026 |
|
- Rougelsum: 21.4278 |
|
- Gen Len: 86.2560 |
|
|
|
## 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: 0.001 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 1.2503 | 1.0 | 184670 | 1.2439 | 20.2525 | 9.1467 | 19.7454 | 19.771 | 87.1766 | |
|
| 1.1629 | 2.0 | 369340 | 1.1773 | 21.0068 | 9.6691 | 20.4565 | 20.4888 | 89.6074 | |
|
| 1.1087 | 3.0 | 554010 | 1.1431 | 21.0216 | 9.6545 | 20.489 | 20.5108 | 85.5895 | |
|
| 1.056 | 4.0 | 738680 | 1.1247 | 21.6776 | 10.1424 | 21.09 | 21.1168 | 89.6576 | |
|
| 1.0199 | 5.0 | 923350 | 1.1179 | 21.6563 | 10.0965 | 21.0814 | 21.1056 | 89.2454 | |
|
| 0.9652 | 6.0 | 1108020 | 1.1122 | 21.6209 | 10.0725 | 21.0623 | 21.0864 | 86.7079 | |
|
| 0.92 | 7.0 | 1292690 | 1.1136 | 21.9396 | 10.2734 | 21.3465 | 21.3745 | 86.5547 | |
|
| 0.8804 | 8.0 | 1477360 | 1.1228 | 21.8457 | 10.1858 | 21.2552 | 21.278 | 87.6413 | |
|
| 0.8447 | 9.0 | 1662030 | 1.1327 | 21.92 | 10.2635 | 21.3415 | 21.3633 | 86.4453 | |
|
| 0.7678 | 10.0 | 1846700 | 1.1442 | 21.9857 | 10.2876 | 21.4026 | 21.4278 | 86.2560 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.12.0 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
