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---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- summary
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
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. -->
# results
This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9889
- Rouge1: 37.6658
- Rouge2: 25.8954
- Rougel: 30.7965
- Rougelsum: 30.7895
## 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: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.8494 | 0.9888 | 55 | 2.2040 | 35.3021 | 24.7331 | 29.5323 | 29.5469 |
| 2.3422 | 1.9955 | 111 | 2.0275 | 37.3011 | 25.7964 | 30.7416 | 30.7363 |
| 2.2332 | 2.9663 | 165 | 1.9889 | 37.6658 | 25.8954 | 30.7965 | 30.7895 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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