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---
library_name: peft
tags:
- generated_from_trainer
base_model: d0rj/rut5-base-summ
metrics:
- rouge
model-index:
- name: summary_about_me
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_about_me
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: 0.9918
- Rouge1: 0.9677
- Rouge2: 0.8966
- Rougel: 0.9677
- Rougelsum: 0.9677
- Gen Len: 79.0
## 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 | 50 | 1.3458 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
| No log | 2.0 | 100 | 1.3283 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
| No log | 3.0 | 150 | 1.3000 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| No log | 4.0 | 200 | 1.2688 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| No log | 5.0 | 250 | 1.2354 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| No log | 6.0 | 300 | 1.2041 | 0.0 | 0.0 | 0.0 | 0.0 | 20.0 |
| No log | 7.0 | 350 | 1.1791 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
| No log | 8.0 | 400 | 1.1403 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| No log | 9.0 | 450 | 1.1153 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| 2.0999 | 10.0 | 500 | 1.0938 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| 2.0999 | 11.0 | 550 | 1.0813 | 0.0 | 0.0 | 0.0 | 0.0 | 17.0 |
| 2.0999 | 12.0 | 600 | 1.0607 | 0.1176 | 0.0 | 0.1176 | 0.1176 | 35.0 |
| 2.0999 | 13.0 | 650 | 1.0508 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
| 2.0999 | 14.0 | 700 | 1.0386 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
| 2.0999 | 15.0 | 750 | 1.0293 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
| 2.0999 | 16.0 | 800 | 1.0210 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
| 2.0999 | 17.0 | 850 | 1.0151 | 0.9333 | 0.8571 | 0.9333 | 0.9333 | 44.0 |
| 2.0999 | 18.0 | 900 | 1.0084 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 |
| 2.0999 | 19.0 | 950 | 1.0039 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 20.0 | 1000 | 0.9999 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 21.0 | 1050 | 0.9963 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 22.0 | 1100 | 0.9943 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 23.0 | 1150 | 0.9932 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 24.0 | 1200 | 0.9925 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
| 1.8806 | 25.0 | 1250 | 0.9918 | 0.9677 | 0.8966 | 0.9677 | 0.9677 | 79.0 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |