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dmWM-Qwen-Qwen2.5-Math-1.5B-Instruct-LucieFr-Al4-OWT-TV – AI Model by Grogros | AlphaNeural AI

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Grogros/
dmWM-Qwen-Qwen2.5-Math-1.5B-Instruct-LucieFr-Al4-OWT-TV

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0

text-generation

generated_from_trainer

Qwen/Qwen2.5-Math-1.5B-Instruct

autotrain_compatible

text-generation-inference

endpoints_compatible

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dmWM-Qwen-Qwen2.5-Math-1.5B-Instruct-LucieFr-Al4-OWT-TV

This model is a fine-tuned version of Qwen/Qwen2.5-Math-1.5B-Instruct on the None 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: 2e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
training_steps: 2500

Training results

Framework versions

Transformers 4.46.3
Pytorch 2.7.1+cu128
Datasets 3.6.0
Tokenizers 0.20.4