transformers tensorboard safetensors mt5 text2text-generation generated_from_trainer base_model:csebuetnlp/mT5_multilingual_XLSum autotrain_compatible endpoints_compatible region:us
---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: deed-summarization_version_5
  results: []
---

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# deed-summarization_version_5

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: 1.2110
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 72.0323

## 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
- lr_scheduler_warmup_steps: 5000
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.5903        | 1.0   | 232  | 3.5371          | 0.0    | 0.0    | 0.0    | 0.0       | 35.1659 |
| 2.577         | 2.0   | 464  | 2.2487          | 0.0    | 0.0    | 0.0    | 0.0       | 49.875  |
| 1.6168        | 3.0   | 696  | 1.8681          | 0.0    | 0.0    | 0.0    | 0.0       | 58.2522 |
| 1.7148        | 4.0   | 928  | 1.6086          | 0.0    | 0.0    | 0.0    | 0.0       | 56.8362 |
| 1.9433        | 5.0   | 1160 | 1.3949          | 0.0    | 0.0    | 0.0    | 0.0       | 62.3427 |
| 1.6744        | 6.0   | 1392 | 1.2110          | 0.0    | 0.0    | 0.0    | 0.0       | 72.0323 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
