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

# summary_vacancy

This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9030
- Rouge1: 0.2908
- Rouge2: 0.0952
- Rougel: 0.2728
- Rougelsum: 0.2728
- Gen Len: 65.6667

## 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: 2e-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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 60   | 2.7805          | 0.4024 | 0.1111 | 0.3511 | 0.3511    | 70.3333 |
| No log        | 2.0   | 120  | 2.7797          | 0.1746 | 0.0    | 0.127  | 0.127     | 34.3333 |
| No log        | 3.0   | 180  | 2.7807          | 0.2222 | 0.0    | 0.1746 | 0.1746    | 38.0    |
| No log        | 4.0   | 240  | 2.7872          | 0.3966 | 0.1524 | 0.349  | 0.349     | 46.6667 |
| No log        | 5.0   | 300  | 2.7995          | 0.2758 | 0.1176 | 0.2758 | 0.2758    | 50.3333 |
| No log        | 6.0   | 360  | 2.8120          | 0.2758 | 0.1176 | 0.2758 | 0.2758    | 49.3333 |
| No log        | 7.0   | 420  | 2.8270          | 0.2758 | 0.1176 | 0.2758 | 0.2758    | 51.0    |
| No log        | 8.0   | 480  | 2.8371          | 0.2758 | 0.1176 | 0.2758 | 0.2758    | 47.6667 |
| 1.9576        | 9.0   | 540  | 2.8480          | 0.2728 | 0.1143 | 0.2728 | 0.2728    | 73.3333 |
| 1.9576        | 10.0  | 600  | 2.8573          | 0.2804 | 0.1333 | 0.2804 | 0.2804    | 63.6667 |
| 1.9576        | 11.0  | 660  | 2.8661          | 0.2888 | 0.1333 | 0.2888 | 0.2888    | 48.6667 |
| 1.9576        | 12.0  | 720  | 2.8718          | 0.2787 | 0.1081 | 0.2787 | 0.2787    | 51.0    |
| 1.9576        | 13.0  | 780  | 2.8786          | 0.1075 | 0.0    | 0.1075 | 0.1075    | 49.6667 |
| 1.9576        | 14.0  | 840  | 2.8817          | 0.2827 | 0.1333 | 0.2827 | 0.2827    | 57.3333 |
| 1.9576        | 15.0  | 900  | 2.8865          | 0.293  | 0.1333 | 0.293  | 0.293     | 39.0    |
| 1.9576        | 16.0  | 960  | 2.8900          | 0.2997 | 0.1333 | 0.2997 | 0.2997    | 57.6667 |
| 1.7164        | 17.0  | 1020 | 2.8941          | 0.2997 | 0.1333 | 0.2997 | 0.2997    | 71.6667 |
| 1.7164        | 18.0  | 1080 | 2.8968          | 0.2997 | 0.1143 | 0.2997 | 0.2997    | 76.3333 |
| 1.7164        | 19.0  | 1140 | 2.8983          | 0.293  | 0.1143 | 0.275  | 0.275     | 88.6667 |
| 1.7164        | 20.0  | 1200 | 2.8998          | 0.3194 | 0.0926 | 0.3019 | 0.3019    | 77.3333 |
| 1.7164        | 21.0  | 1260 | 2.9005          | 0.2908 | 0.0952 | 0.2728 | 0.2728    | 65.6667 |
| 1.7164        | 22.0  | 1320 | 2.9020          | 0.2908 | 0.0952 | 0.2728 | 0.2728    | 65.6667 |
| 1.7164        | 23.0  | 1380 | 2.9027          | 0.2908 | 0.0952 | 0.2728 | 0.2728    | 65.6667 |
| 1.7164        | 24.0  | 1440 | 2.9026          | 0.2908 | 0.0952 | 0.2728 | 0.2728    | 65.6667 |
| 1.647         | 25.0  | 1500 | 2.9030          | 0.2908 | 0.0952 | 0.2728 | 0.2728    | 65.6667 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2