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---
license: mit
base_model: cointegrated/rut5-base-absum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flux-dsum
  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. -->

# flux-dsum

This model is a fine-tuned version of [cointegrated/rut5-base-absum](https://huggingface.co/cointegrated/rut5-base-absum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3535
- Rouge1: 0.3631
- Rouge2: 0.1695
- Rougel: 0.325
- Rougelsum: 0.3251
- Gen Len: 18.2008

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7402        | 1.0   | 21753 | 1.4456          | 0.3492 | 0.1601 | 0.3112 | 0.3114    | 18.0104 |
| 1.59          | 2.0   | 43506 | 1.3912          | 0.3569 | 0.1616 | 0.3186 | 0.3187    | 18.1955 |
| 1.5522        | 3.0   | 65259 | 1.3675          | 0.3607 | 0.1682 | 0.3231 | 0.3233    | 18.1123 |
| 1.5162        | 4.0   | 87012 | 1.3535          | 0.3631 | 0.1695 | 0.325  | 0.3251    | 18.2008 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1