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---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mT5-lithuanian-simplifier
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. -->
# mT5-lithuanian-simplifier
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0687
- Rouge1: 0.7322
- Rouge2: 0.5833
- Rougel: 0.7261
- Gen Len: 34.6325
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| 23.3756 | 0.48 | 200 | 16.6054 | 0.011 | 0.0006 | 0.0105 | 512.0 |
| 1.435 | 0.96 | 400 | 0.5767 | 0.1436 | 0.0387 | 0.1307 | 39.0358 |
| 0.2269 | 1.44 | 600 | 0.1658 | 0.4744 | 0.317 | 0.4631 | 34.6325 |
| 0.1709 | 1.91 | 800 | 0.1030 | 0.5865 | 0.4231 | 0.577 | 34.6325 |
| 0.1311 | 2.39 | 1000 | 0.0923 | 0.6245 | 0.4626 | 0.6173 | 34.6325 |
| 0.1196 | 2.87 | 1200 | 0.0851 | 0.6759 | 0.5159 | 0.6681 | 34.6325 |
| 0.1156 | 3.35 | 1400 | 0.0761 | 0.6927 | 0.5288 | 0.6845 | 34.6325 |
| 0.0897 | 3.83 | 1600 | 0.0756 | 0.698 | 0.5352 | 0.6906 | 34.6325 |
| 0.1149 | 4.31 | 1800 | 0.0738 | 0.7085 | 0.55 | 0.7022 | 34.6325 |
| 0.0967 | 4.78 | 2000 | 0.0725 | 0.7187 | 0.5632 | 0.712 | 34.6325 |
| 0.1097 | 5.26 | 2200 | 0.0703 | 0.7214 | 0.5645 | 0.7143 | 34.6325 |
| 0.0852 | 5.74 | 2400 | 0.0708 | 0.7241 | 0.5724 | 0.7176 | 34.6325 |
| 0.0537 | 6.22 | 2600 | 0.0693 | 0.7285 | 0.578 | 0.7217 | 34.6325 |
| 0.0866 | 6.7 | 2800 | 0.0698 | 0.7277 | 0.5795 | 0.7216 | 34.6325 |
| 0.0692 | 7.18 | 3000 | 0.0685 | 0.7336 | 0.5849 | 0.7274 | 34.6325 |
| 0.0786 | 7.66 | 3200 | 0.0687 | 0.7322 | 0.5833 | 0.7261 | 34.6325 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0
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