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: HappyNews_1_loadbest
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# HappyNews_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: 3.1967

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1092        | 0.29  | 100  | 4.0260          |
| 4.3545        | 0.58  | 200  | 3.6022          |
| 3.818         | 0.87  | 300  | 3.3815          |
| 3.2577        | 1.16  | 400  | 3.2590          |
| 3.1005        | 1.45  | 500  | 3.1290          |
| 3.0309        | 1.73  | 600  | 3.0690          |
| 3.0128        | 2.02  | 700  | 3.0172          |
| 2.4054        | 2.31  | 800  | 3.0086          |
| 2.7848        | 2.6   | 900  | 3.0103          |
| 2.4307        | 2.89  | 1000 | 2.9606          |
| 2.3408        | 3.18  | 1100 | 2.9490          |
| 2.4232        | 3.47  | 1200 | 2.9333          |
| 2.5301        | 3.76  | 1300 | 2.9138          |
| 1.9984        | 4.05  | 1400 | 2.9422          |
| 2.1215        | 4.34  | 1500 | 2.9620          |
| 1.859         | 4.62  | 1600 | 2.9550          |
| 1.8986        | 4.91  | 1700 | 2.9654          |
| 1.847         | 5.2   | 1800 | 3.0660          |
| 1.7843        | 5.49  | 1900 | 3.0169          |
| 1.9724        | 5.78  | 2000 | 3.0131          |
| 1.6603        | 6.07  | 2100 | 3.0816          |
| 1.4024        | 6.36  | 2200 | 3.0947          |
| 1.2758        | 6.65  | 2300 | 3.0688          |
| 1.7435        | 6.94  | 2400 | 3.0203          |
| 1.2973        | 7.23  | 2500 | 3.1221          |
| 1.282         | 7.51  | 2600 | 3.1566          |
| 1.4837        | 7.8   | 2700 | 3.1047          |
| 1.6313        | 8.09  | 2800 | 3.1343          |
| 1.4611        | 8.38  | 2900 | 3.1634          |
| 1.0115        | 8.67  | 3000 | 3.1751          |
| 1.4337        | 8.96  | 3100 | 3.1701          |
| 1.1845        | 9.25  | 3200 | 3.1881          |
| 1.2019        | 9.54  | 3300 | 3.1998          |
| 1.1448        | 9.83  | 3400 | 3.1967          |


### Framework versions

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