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

This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the meta_toy_2k 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
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• total_eval_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 4.0

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	36	0.3713
No log	2.0	72	0.1436
0.4266	3.0	108	0.0750
0.4266	4.0	144	0.0680

Framework versions

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