byt5-base-ko-1e4-jit-20epochs-a100-jamoparams-wu2000-rm1-bs2-ga64-eb128-distilled-base-5

This model is a fine-tuned version of google/byt5-small on an unknown dataset. It achieves the following results on the evaluation set:

• epoch: 30.0
• eval_loss: 1.0565
• eval_runtime: 44.7587
• eval_samples_per_second: 111.71
• eval_steps_per_second: 27.928
• step: 37590

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: 0.0005
• train_batch_size: 2
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 64
• total_train_batch_size: 128
• optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: inverse_sqrt
• lr_scheduler_warmup_steps: 2000
• num_epochs: 40
• label_smoothing_factor: 0.1

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.1+cu128
• Datasets 4.4.1
• Tokenizers 0.22.1