This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the deepmath_sft_1024 dataset. It achieves the following results on the evaluation set:

Loss: 0.6684

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: 4
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 64
total_eval_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH 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: 0.05
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.4883	2.9481	200	0.6684

Framework versions

Transformers 4.57.1
Pytorch 2.4.1+cu124
Datasets 4.0.0
Tokenizers 0.22.2

tengfeima-ai/Qwen2.5-0.5B-Math-SFT-1024

sft_1024_qwen25_0.5b

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tengfeima-ai/
Qwen2.5-0.5B-Math-SFT-1024