---
base_model: transformer3/H2-keywordextractor
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: H2-keywordextractor-finetuned-scope-summarization
  results: []
---

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# 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