metacog0/qwen2.5-7b-ins-lora-50-toy-meta

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qwen2.5-7b-ins-lora-50-toy-meta

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the metatoy2k dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0680

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: 0.0001
• —trainbatchsize: 1
• —evalbatchsize: 1
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 8
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 64
• —totalevalbatch_size: 8
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 4.0

Training results

Framework versions

• —PEFT 0.15.2
• —Transformers 4.55.0
• —Pytorch 2.8.0+cu128
• —Datasets 3.6.0
• —Tokenizers 0.21.1