---
base_model: d0rj/rut5-base-summ
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: rut5-base-summ-dialogsum
  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. -->

# rut5-base-summ-dialogsum

This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1263
- Rouge1: 33.5111
- Rouge2: 0.1696
- Rougel: 33.4559
- Rougelsum: 33.4934
- Gen Len: 4.1546

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.0946        | 1.0   | 786   | 1.7462          | 45.4252 | 0.0    | 45.4009 | 45.4139   | 4.0464  |
| 1.7182        | 2.0   | 1572  | 1.5005          | 44.9295 | 0.0    | 44.9183 | 44.9108   | 4.1126  |
| 1.5304        | 3.0   | 2358  | 1.3826          | 39.5888 | 0.0    | 39.5811 | 39.5646   | 4.1698  |
| 1.4261        | 4.0   | 3144  | 1.3121          | 30.1735 | 0.0    | 30.1127 | 30.1415   | 4.1520  |
| 1.3252        | 5.0   | 3930  | 1.2641          | 35.7738 | 0.0    | 35.7408 | 35.7858   | 3.8791  |
| 1.2878        | 6.0   | 4716  | 1.2353          | 33.0773 | 0.0    | 32.9682 | 33.0551   | 3.7252  |
| 1.2068        | 7.0   | 5502  | 1.2051          | 34.4094 | 0.0    | 34.3902 | 34.3884   | 3.7729  |
| 1.1763        | 8.0   | 6288  | 1.1952          | 33.0914 | 0.1908 | 33.0267 | 33.0472   | 3.9739  |
| 1.1346        | 9.0   | 7074  | 1.1798          | 33.9606 | 0.0    | 33.9335 | 33.979    | 4.1768  |
| 1.1044        | 10.0  | 7860  | 1.1632          | 32.9529 | 0.0    | 32.9367 | 32.9396   | 4.1673  |
| 1.1073        | 11.0  | 8646  | 1.1499          | 34.0904 | 0.0    | 34.0659 | 34.1317   | 4.1934  |
| 1.0619        | 12.0  | 9432  | 1.1516          | 32.9502 | 0.0    | 32.9056 | 32.9376   | 4.0312  |
| 1.0365        | 13.0  | 10218 | 1.1478          | 31.68   | 0.0    | 31.6488 | 31.7003   | 4.0293  |
| 1.0161        | 14.0  | 11004 | 1.1427          | 32.6651 | 0.0424 | 32.6345 | 32.6538   | 4.1113  |
| 0.9805        | 15.0  | 11790 | 1.1343          | 34.0304 | 0.0636 | 33.9433 | 33.999    | 4.0674  |
| 0.9661        | 16.0  | 12576 | 1.1309          | 34.8704 | 0.0848 | 34.8014 | 34.8501   | 4.0681  |
| 0.9511        | 17.0  | 13362 | 1.1348          | 32.8744 | 0.0    | 32.8277 | 32.8547   | 4.1081  |
| 0.9392        | 18.0  | 14148 | 1.1326          | 32.9349 | 0.1908 | 32.8895 | 32.9376   | 4.2627  |
| 0.9341        | 19.0  | 14934 | 1.1263          | 33.5111 | 0.1696 | 33.4559 | 33.4934   | 4.1546  |
| 0.9396        | 20.0  | 15720 | 1.1349          | 33.9121 | 0.2545 | 33.8438 | 33.8993   | 4.1705  |
| 0.9314        | 21.0  | 16506 | 1.1276          | 33.0779 | 0.106  | 33.0546 | 33.0903   | 4.1399  |
| 0.8987        | 22.0  | 17292 | 1.1333          | 33.8566 | 0.1696 | 33.7943 | 33.843    | 4.1419  |
| 0.8895        | 23.0  | 18078 | 1.1343          | 33.6108 | 0.1484 | 33.5738 | 33.636    | 4.2328  |
| 0.8847        | 24.0  | 18864 | 1.1355          | 33.4257 | 0.2757 | 33.3804 | 33.4495   | 4.1711  |
| 0.8832        | 25.0  | 19650 | 1.1355          | 33.6211 | 0.3393 | 33.5937 | 33.636    | 4.1959  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0