---
base_model: csebuetnlp/mT5_multilingual_XLSum
tags:
- generated_from_trainer
model-index:
- name: type2_neg_1
  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. -->

# type2_neg_1

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: 3.0065

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 3.7124        | 0.49  | 500   | 3.2054          |
| 3.3429        | 0.98  | 1000  | 2.9874          |
| 2.9583        | 1.47  | 1500  | 2.9013          |
| 3.0351        | 1.96  | 2000  | 2.8271          |
| 2.5532        | 2.46  | 2500  | 2.8162          |
| 2.5494        | 2.95  | 3000  | 2.8092          |
| 2.5826        | 3.44  | 3500  | 2.8252          |
| 2.0509        | 3.93  | 4000  | 2.8108          |
| 2.1758        | 4.42  | 4500  | 2.8365          |
| 1.9913        | 4.91  | 5000  | 2.8331          |
| 1.5736        | 5.4   | 5500  | 2.9037          |
| 2.3872        | 5.89  | 6000  | 2.8933          |
| 1.758         | 6.39  | 6500  | 2.9362          |
| 1.6921        | 6.88  | 7000  | 2.9323          |
| 1.7101        | 7.37  | 7500  | 2.9635          |
| 1.6037        | 7.86  | 8000  | 2.9728          |
| 1.3991        | 8.35  | 8500  | 3.0027          |
| 1.5043        | 8.84  | 9000  | 2.9930          |
| 1.808         | 9.33  | 9500  | 3.0045          |
| 1.4231        | 9.82  | 10000 | 3.0065          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2