---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- generated_from_trainer
model-index:
- name: SadNews_2_20epochs
  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. -->

# SadNews_2_20epochs

This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co./csebuetnlp/mT5_multilingual_XLSum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2760

## 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: 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: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.3998        | 0.76  | 500   | 2.8591          |
| 2.8316        | 1.52  | 1000  | 2.5640          |
| 2.3969        | 2.29  | 1500  | 2.4411          |
| 1.8762        | 3.05  | 2000  | 2.4241          |
| 1.9914        | 3.81  | 2500  | 2.3928          |
| 1.8294        | 4.57  | 3000  | 2.4093          |
| 1.7505        | 5.34  | 3500  | 2.4674          |
| 1.313         | 6.1   | 4000  | 2.5457          |
| 1.5311        | 6.86  | 4500  | 2.4944          |
| 1.2645        | 7.62  | 5000  | 2.5876          |
| 1.0581        | 8.38  | 5500  | 2.6490          |
| 1.2508        | 9.15  | 6000  | 2.7311          |
| 1.3671        | 9.91  | 6500  | 2.7163          |
| 0.9799        | 10.67 | 7000  | 2.7751          |
| 1.03          | 11.43 | 7500  | 2.8911          |
| 0.8382        | 12.2  | 8000  | 2.9649          |
| 1.0784        | 12.96 | 8500  | 2.9205          |
| 0.7969        | 13.72 | 9000  | 3.0321          |
| 0.7965        | 14.48 | 9500  | 3.0564          |
| 0.7737        | 15.24 | 10000 | 3.1322          |
| 0.591         | 16.01 | 10500 | 3.1051          |
| 0.8767        | 16.77 | 11000 | 3.1922          |
| 0.6458        | 17.53 | 11500 | 3.2355          |
| 0.591         | 18.29 | 12000 | 3.2301          |
| 0.6428        | 19.05 | 12500 | 3.2603          |
| 0.7789        | 19.82 | 13000 | 3.2760          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2