asm2asm-qwen2.5coder-0.5b-100k-2ep-tokenizer

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-0.5B-Instruct on an unknown dataset.

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: 0.0002
• train_batch_size: 1
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Framework versions

• Transformers 4.46.0
• Pytorch 2.4.1+cu118
• Datasets 3.0.1
• Tokenizers 0.20.1