KingLTD's picture
End of training
a366fdb
metadata
license: mit
base_model: VietAI/vit5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: pretrain_Law_model_vit5_version1
    results: []

pretrain_Law_model_vit5_version1

This model is a fine-tuned version of VietAI/vit5-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2779
  • Rouge1: 0.4859
  • Rouge2: 0.3617
  • Rougel: 0.4218
  • Rougelsum: 0.4417

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
No log 1.0 245 0.3566 0.4739 0.3369 0.4053 0.4273
No log 2.0 490 0.3240 0.4752 0.3453 0.4095 0.4300
0.7518 3.0 735 0.3059 0.4760 0.3510 0.4112 0.4311
0.7518 4.0 980 0.2951 0.4838 0.3584 0.4164 0.4387
0.2808 5.0 1225 0.2858 0.4799 0.3582 0.4166 0.4368
0.2808 6.0 1470 0.2831 0.4839 0.3611 0.4194 0.4403
0.2351 7.0 1715 0.2814 0.4858 0.3644 0.4218 0.4423
0.2351 8.0 1960 0.2779 0.4850 0.3612 0.4206 0.4416
0.2074 9.0 2205 0.2775 0.4836 0.3590 0.4199 0.4398
0.2074 10.0 2450 0.2779 0.4859 0.3617 0.4218 0.4417

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3