RichardErkhov/ahmedheakl_-_qwen2.5_0.5b_1M_stack_16kcw_2ep-gguf

Quantization made by Richard Erkhov.

Github

Discord

Request more models

qwen2.50.5b1Mstack16kcw_2ep - GGUF

• —Model creator: https://huggingface.co/ahmedheakl/
• —Original model: https://huggingface.co/ahmedheakl/qwen2.50.5b1Mstack16kcw_2ep/

Original model description: --- libraryname: transformers license: apache-2.0 basemodel: Qwen/Qwen2.5-Coder-0.5B-Instruct tags:

• —llama-factory
• —full
• —generatedfromtrainer model-index:
• —name: qwen2.50.5b1Mstack16kcw_2ep results: [] ---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

qwen2.50.5b1Mstack16kcw_2ep

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-0.5B-Instruct on the anghabench1M1, the anghabench1M2 and the stack datasets. It achieves the following results on the evaluation set:

• —Loss: 0.0020

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: 1e-05
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 8
• —totalevalbatch_size: 4
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 2.0

Training results

Framework versions

• —Transformers 4.46.1
• —Pytorch 2.5.1+cu124
• —Datasets 3.1.0
• —Tokenizers 0.20.3