CoolFace
Modelpublic

RichardErkhov/cutelemonlili_-_Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview-gguf

sourceHugging Faceupdated 1y agoView on Hugging Face
0likes662downloads
Model Card

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Phi-3.5-mini-instructMATHtrainingQwenQwQ32BPreview - GGUF

  • —Model creator: https://huggingface.co/cutelemonlili/
  • —Original model: https://huggingface.co/cutelemonlili/Phi-3.5-mini-instructMATHtrainingQwenQwQ32BPreview/
NameQuant methodSize
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q2_K.ggufQ2_K1.32GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.IQ3_XS.ggufIQ3_XS1.51GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.IQ3_S.ggufIQ3_S1.57GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q3_K_S.ggufQ3KS1.57GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.IQ3_M.ggufIQ3_M1.73GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q3_K.ggufQ3_K1.82GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q3_K_M.ggufQ3KM1.82GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q3_K_L.ggufQ3KL1.94GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.IQ4_XS.ggufIQ4_XS1.93GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q4_0.ggufQ4_02.03GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.IQ4_NL.ggufIQ4_NL2.04GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q4_K_S.ggufQ4KS2.04GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q4_K.ggufQ4_K2.23GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q4_K_M.ggufQ4KM2.23GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q4_1.ggufQ4_12.24GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q5_0.ggufQ5_02.46GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q5_K_S.ggufQ5KS2.46GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q5_K.ggufQ5_K2.62GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q5_K_M.ggufQ5KM2.62GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q5_1.ggufQ5_12.68GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q6_K.ggufQ6_K2.92GB
Phi-3.5-mini-instruct_MATH_training_Qwen_QwQ_32B_Preview.Q8_0.ggufQ8_03.78GB

Original model description: --- libraryname: transformers license: other basemodel: microsoft/Phi-3.5-mini-instruct tags:

  • —llama-factory
  • —full
  • —generatedfromtrainer model-index:
  • —name: MATHtrainingQwenQwQ32B_Preview 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. -->

MATHtrainingQwenQwQ32B_Preview

This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on the MATHtrainingQwenQwQ32B_Preview dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.2987

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: 2
  • —evalbatchsize: 1
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —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
  • —num_epochs: 2

Training results

Training LossEpochStepValidation Loss
0.2760.29992000.3213
0.29570.59974000.3050
0.35590.89966000.2940
0.23481.19948000.3035
0.18421.499310000.3000
0.15111.799112000.2996

Framework versions

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