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---

library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: mt5_base_TH_wiki
  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. -->

# mt5_base_TH_wiki



This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.

It achieves the following results on the evaluation set:

- Loss: nan

- Rouge2 Precision: 0.0021

- Rouge2 Recall: 0.0009

- Rouge2 Fmeasure: 0.0013



## 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: 50
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |

|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|

| 0.0           | 1.0   | 1296  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 2.0   | 2592  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 3.0   | 3888  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 4.0   | 5184  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 5.0   | 6480  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 6.0   | 7776  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 7.0   | 9072  | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 8.0   | 10368 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 9.0   | 11664 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 10.0  | 12960 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 11.0  | 14256 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 12.0  | 15552 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 13.0  | 16848 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 14.0  | 18144 | nan             | 0.0021           | 0.0009        | 0.0013          |

| 0.0           | 15.0  | 19440 | nan             | 0.0021           | 0.0009        | 0.0013          |





### Framework versions



- Transformers 4.46.1

- Pytorch 2.2.2

- Datasets 2.16.1

- Tokenizers 0.20.1