README.md

metadata

library_name: transformers
license: mit
base_model: VietAI/vit5-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
model-index:
  - name: ViNormT5
    results: []

ViNormT5

This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2401
• Bleu Score: 78.0055
• Precision: 51.2545
• Recall: 51.2545
• Gen Len: 12.7897
• Err: 51.2545

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu Score	Precision	Recall	Gen Len	Err
0.4488	1.0	1675	0.2401	78.0055	51.2545	51.2545	12.7897	51.2545

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0