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---
base_model: UrukHan/t5-russian-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-russian-summarization
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/kornilova_eka/huggingface/runs/qlwnr551)
# t5-russian-summarization
This model is a fine-tuned version of [UrukHan/t5-russian-summarization](https://huggingface.co/UrukHan/t5-russian-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6100
- Rouge1: 14.6206
- Rouge2: 3.6976
- Rougel: 14.7351
- Rougelsum: 14.6463
- Gen Len: 15.3711
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 1.63 | 0.1769 | 5000 | 1.6100 | 14.6206 | 3.6976 | 14.7351 | 14.6463 | 15.3711 |
| 1.6458 | 0.3538 | 10000 | 1.6100 | 14.6206 | 3.6976 | 14.7351 | 14.6463 | 15.3711 |
| 1.6401 | 0.5306 | 15000 | 1.6100 | 14.6206 | 3.6976 | 14.7351 | 14.6463 | 15.3711 |
| 1.6504 | 0.7075 | 20000 | 1.6100 | 14.6206 | 3.6976 | 14.7351 | 14.6463 | 15.3711 |
| 1.6104 | 0.8844 | 25000 | 1.6100 | 14.6206 | 3.6976 | 14.7351 | 14.6463 | 15.3711 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.0.1
- Datasets 2.20.0
- Tokenizers 0.19.1
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