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
model-index:
- name: GeneralNews_1_loadbest
  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. -->

# GeneralNews_1_loadbest

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: 2.9834

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1541        | 0.25  | 200  | 3.4209          |
| 3.5494        | 0.51  | 400  | 3.1702          |
| 3.2618        | 0.76  | 600  | 3.0273          |
| 3.5983        | 1.01  | 800  | 2.9550          |
| 3.3355        | 1.26  | 1000 | 2.8883          |
| 3.4976        | 1.52  | 1200 | 2.8653          |
| 3.1001        | 1.77  | 1400 | 2.8543          |
| 2.282         | 2.02  | 1600 | 2.7953          |
| 2.5724        | 2.27  | 1800 | 2.7866          |
| 2.7474        | 2.53  | 2000 | 2.7778          |
| 3.0323        | 2.78  | 2200 | 2.7901          |
| 2.3032        | 3.03  | 2400 | 2.7641          |
| 2.5042        | 3.28  | 2600 | 2.8059          |
| 1.9857        | 3.54  | 2800 | 2.7847          |
| 2.5909        | 3.79  | 3000 | 2.8045          |
| 2.2105        | 4.04  | 3200 | 2.8051          |
| 2.1151        | 4.29  | 3400 | 2.8331          |
| 1.9858        | 4.55  | 3600 | 2.8292          |
| 1.9633        | 4.8   | 3800 | 2.8133          |
| 2.0282        | 5.05  | 4000 | 2.8317          |
| 2.0988        | 5.3   | 4200 | 2.8781          |
| 2.0699        | 5.56  | 4400 | 2.8627          |
| 2.1769        | 5.81  | 4600 | 2.8388          |
| 1.7436        | 6.06  | 4800 | 2.8899          |
| 1.8312        | 6.31  | 5000 | 2.9223          |
| 1.841         | 6.57  | 5200 | 2.8970          |
| 2.0157        | 6.82  | 5400 | 2.8754          |
| 2.1223        | 7.07  | 5600 | 2.8958          |
| 1.6103        | 7.32  | 5800 | 2.9247          |
| 1.7702        | 7.58  | 6000 | 2.9562          |
| 1.537         | 7.83  | 6200 | 2.9597          |
| 1.933         | 8.08  | 6400 | 2.9585          |
| 1.3947        | 8.33  | 6600 | 2.9841          |
| 1.639         | 8.59  | 6800 | 2.9723          |
| 1.6441        | 8.84  | 7000 | 2.9770          |
| 1.4509        | 9.09  | 7200 | 2.9865          |
| 1.6212        | 9.34  | 7400 | 2.9890          |
| 1.8013        | 9.6   | 7600 | 2.9877          |
| 1.3722        | 9.85  | 7800 | 2.9834          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
