tensorboard safetensors generated_from_trainer base_model:d0rj/rut5-base-summ region:us
---
base_model: d0rj/rut5-base-summ
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summary1
  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. -->

# summary1

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: 2.4999
- Rouge1: 0.1582
- Rouge2: 0.0671
- Rougel: 0.1582
- Rougelsum: 0.156
- Gen Len: 46.7

## 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   | 2.4990          | 0.0834 | 0.0133 | 0.0858 | 0.0847    | 37.0    |
| No log        | 2.0   | 180  | 2.4853          | 0.1484 | 0.0411 | 0.1431 | 0.1405    | 46.7    |
| No log        | 3.0   | 270  | 2.4740          | 0.0753 | 0.0133 | 0.074  | 0.074     | 50.2    |
| No log        | 4.0   | 360  | 2.4672          | 0.1468 | 0.0575 | 0.1472 | 0.14      | 53.9    |
| No log        | 5.0   | 450  | 2.4647          | 0.1743 | 0.0824 | 0.1741 | 0.1694    | 46.1    |
| 1.6637        | 6.0   | 540  | 2.4651          | 0.1702 | 0.0436 | 0.1702 | 0.1658    | 48.3    |
| 1.6637        | 7.0   | 630  | 2.4683          | 0.1658 | 0.0545 | 0.1658 | 0.1606    | 48.7    |
| 1.6637        | 8.0   | 720  | 2.4716          | 0.1743 | 0.0545 | 0.1741 | 0.1694    | 46.2    |
| 1.6637        | 9.0   | 810  | 2.4758          | 0.1743 | 0.0545 | 0.1741 | 0.1694    | 48.2    |
| 1.6637        | 10.0  | 900  | 2.4780          | 0.1641 | 0.0678 | 0.1643 | 0.1593    | 50.0    |
| 1.6637        | 11.0  | 990  | 2.4819          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.4    |
| 1.3794        | 12.0  | 1080 | 2.4854          | 0.1621 | 0.0708 | 0.1621 | 0.1599    | 47.3    |
| 1.3794        | 13.0  | 1170 | 2.4875          | 0.1562 | 0.065  | 0.1576 | 0.1521    | 48.4    |
| 1.3794        | 14.0  | 1260 | 2.4886          | 0.1562 | 0.065  | 0.1576 | 0.1521    | 48.5    |
| 1.3794        | 15.0  | 1350 | 2.4908          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.3    |
| 1.3794        | 16.0  | 1440 | 2.4925          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 48.7    |
| 1.2935        | 17.0  | 1530 | 2.4942          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.3    |
| 1.2935        | 18.0  | 1620 | 2.4954          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.3    |
| 1.2935        | 19.0  | 1710 | 2.4971          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.5    |
| 1.2935        | 20.0  | 1800 | 2.4976          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 47.3    |
| 1.2935        | 21.0  | 1890 | 2.4981          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 46.9    |
| 1.2935        | 22.0  | 1980 | 2.4990          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 46.9    |
| 1.236         | 23.0  | 2070 | 2.4996          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 46.7    |
| 1.236         | 24.0  | 2160 | 2.4997          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 46.7    |
| 1.236         | 25.0  | 2250 | 2.4999          | 0.1582 | 0.0671 | 0.1582 | 0.156     | 46.7    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
