---
base_model: d0rj/rut5-base-summ
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summary_resume_keywords
  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_resume_keywords

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: 2.9737
- Rouge1: 0.2285
- Rouge2: 0.1524
- Rougel: 0.2285
- Rougelsum: 0.2285
- Gen Len: 51.3333

## 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   | 90   | 2.7766          | 0.2485 | 0.1111 | 0.2485 | 0.2485    | 52.0    |
| No log        | 2.0   | 180  | 2.7734          | 0.2556 | 0.1404 | 0.2389 | 0.2389    | 53.6667 |
| No log        | 3.0   | 270  | 2.7763          | 0.2882 | 0.1368 | 0.2557 | 0.2557    | 51.6667 |
| No log        | 4.0   | 360  | 2.7921          | 0.2722 | 0.1404 | 0.2389 | 0.2389    | 58.3333 |
| No log        | 5.0   | 450  | 2.8146          | 0.2778 | 0.1622 | 0.2607 | 0.2607    | 57.3333 |
| 2.1351        | 6.0   | 540  | 2.8387          | 0.2778 | 0.1622 | 0.2607 | 0.2607    | 57.3333 |
| 2.1351        | 7.0   | 630  | 2.8569          | 0.2778 | 0.1622 | 0.2607 | 0.2607    | 57.3333 |
| 2.1351        | 8.0   | 720  | 2.8736          | 0.2538 | 0.1524 | 0.2538 | 0.2538    | 55.3333 |
| 2.1351        | 9.0   | 810  | 2.8883          | 0.2538 | 0.1524 | 0.2538 | 0.2538    | 55.3333 |
| 2.1351        | 10.0  | 900  | 2.9025          | 0.2315 | 0.1524 | 0.2315 | 0.2315    | 51.0    |
| 2.1351        | 11.0  | 990  | 2.9161          | 0.2315 | 0.1524 | 0.2315 | 0.2315    | 51.0    |
| 1.7131        | 12.0  | 1080 | 2.9269          | 0.2315 | 0.1524 | 0.2315 | 0.2315    | 51.0    |
| 1.7131        | 13.0  | 1170 | 2.9354          | 0.226  | 0.1524 | 0.226  | 0.226     | 54.0    |
| 1.7131        | 14.0  | 1260 | 2.9427          | 0.226  | 0.1524 | 0.226  | 0.226     | 54.0    |
| 1.7131        | 15.0  | 1350 | 2.9471          | 0.2272 | 0.1524 | 0.2272 | 0.2272    | 53.6667 |
| 1.7131        | 16.0  | 1440 | 2.9509          | 0.226  | 0.1524 | 0.226  | 0.226     | 54.0    |
| 1.5914        | 17.0  | 1530 | 2.9558          | 0.2272 | 0.1524 | 0.2272 | 0.2272    | 53.6667 |
| 1.5914        | 18.0  | 1620 | 2.9589          | 0.226  | 0.1524 | 0.226  | 0.226     | 54.0    |
| 1.5914        | 19.0  | 1710 | 2.9636          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 51.0    |
| 1.5914        | 20.0  | 1800 | 2.9660          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 51.0    |
| 1.5914        | 21.0  | 1890 | 2.9687          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 50.3333 |
| 1.5914        | 22.0  | 1980 | 2.9709          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 50.3333 |
| 1.5508        | 23.0  | 2070 | 2.9736          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 50.3333 |
| 1.5508        | 24.0  | 2160 | 2.9742          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 50.3333 |
| 1.5508        | 25.0  | 2250 | 2.9737          | 0.2285 | 0.1524 | 0.2285 | 0.2285    | 51.3333 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2