Edit model card

Gyeongsang_encoder

This model is a fine-tuned version of gogamza/kobart-base-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0062
  • Bleu: 91.4436
  • Gen Len: 13.3478

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
0.0054 1.0 12910 0.0072 91.1948 13.3484
0.0052 2.0 25820 0.0063 91.3684 13.3464
0.0043 3.0 38730 0.0062 91.4436 13.3478

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
Downloads last month
2
Safetensors
Model size
124M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for yomilimi/Gyeongsang_encoder

Finetuned
(13)
this model
Finetunes
1 model