|
--- |
|
base_model: transformer3/H2-keywordextractor |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: H2-keywordextractor-finetuned-scope-summarization |
|
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. --> |
|
|
|
# H2-keywordextractor-finetuned-scope-summarization |
|
|
|
This model is a fine-tuned version of [transformer3/H2-keywordextractor](https://huggingface.co/transformer3/H2-keywordextractor) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2073 |
|
- Rouge1: 13.0222 |
|
- Rouge2: 10.4851 |
|
- Rougel: 13.0872 |
|
- Rougelsum: 13.1095 |
|
|
|
## 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: 5.6e-05 |
|
- train_batch_size: 15 |
|
- eval_batch_size: 15 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 0.8852 | 1.0 | 23 | 0.3103 | 10.3278 | 6.2988 | 10.3528 | 10.3293 | |
|
| 0.2901 | 2.0 | 46 | 0.2825 | 10.8308 | 7.5214 | 10.8428 | 10.8103 | |
|
| 0.2625 | 3.0 | 69 | 0.2711 | 12.0182 | 8.6415 | 12.0115 | 12.0537 | |
|
| 0.2453 | 4.0 | 92 | 0.2550 | 12.9535 | 9.6936 | 12.9952 | 13.0384 | |
|
| 0.2353 | 5.0 | 115 | 0.2464 | 11.2808 | 7.8603 | 11.3196 | 11.281 | |
|
| 0.2338 | 6.0 | 138 | 0.2389 | 12.6604 | 9.6355 | 12.6519 | 12.6377 | |
|
| 0.2183 | 7.0 | 161 | 0.2307 | 13.2591 | 10.6628 | 13.2399 | 13.2554 | |
|
| 0.2143 | 8.0 | 184 | 0.2252 | 13.537 | 11.1632 | 13.5668 | 13.5957 | |
|
| 0.2055 | 9.0 | 207 | 0.2206 | 13.7032 | 11.6575 | 13.7226 | 13.774 | |
|
| 0.2022 | 10.0 | 230 | 0.2158 | 13.7727 | 11.5365 | 13.7404 | 13.8018 | |
|
| 0.1961 | 11.0 | 253 | 0.2166 | 13.4062 | 11.2919 | 13.4698 | 13.4854 | |
|
| 0.2018 | 12.0 | 276 | 0.2116 | 13.8406 | 11.852 | 13.8309 | 13.8995 | |
|
| 0.1946 | 13.0 | 299 | 0.2131 | 12.5757 | 9.5775 | 12.5738 | 12.6535 | |
|
| 0.1943 | 14.0 | 322 | 0.2142 | 11.617 | 9.0291 | 11.5311 | 11.7201 | |
|
| 0.2068 | 15.0 | 345 | 0.2080 | 12.9136 | 10.2865 | 12.9659 | 12.9787 | |
|
| 0.2051 | 16.0 | 368 | 0.2041 | 13.6492 | 11.6388 | 13.6506 | 13.7041 | |
|
| 0.1887 | 17.0 | 391 | 0.2119 | 11.4317 | 8.2482 | 11.386 | 11.4313 | |
|
| 0.1886 | 18.0 | 414 | 0.2097 | 13.0287 | 10.6547 | 13.0829 | 13.118 | |
|
| 0.1887 | 19.0 | 437 | 0.2079 | 13.0073 | 10.5381 | 13.0514 | 13.1089 | |
|
| 0.186 | 20.0 | 460 | 0.2073 | 13.0222 | 10.4851 | 13.0872 | 13.1095 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.2.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
