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dmWM-Qwen-Qwen2.5-3B-Instruct-ALL – AI Model by Grogros | AlphaNeural AI

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Grogros/
dmWM-Qwen-Qwen2.5-3B-Instruct-ALL

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text-generation

generated_from_trainer

Qwen/Qwen2.5-3B-Instruct

text-generation-inference

endpoints_compatible

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dmWM-Qwen-Qwen2.5-3B-Instruct-OWT-Al4-OMI-LucieFr-HA-WOHealth-Full

This model is a fine-tuned version of Qwen/Qwen2.5-3B-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 4.51.3
Pytorch 2.5.1.post303
Datasets 3.2.0
Tokenizers 0.21.1