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

Loss: 0.0014

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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 8
total_eval_batch_size: 4
optimizer: Use 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: 0.1
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0036	0.4091	25000	0.0026
0.0015	0.8181	50000	0.0015

Framework versions

Transformers 4.46.1
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3

ahmedheakl/qwen2.5_0.5b_llamafac_500k

qwen2.5_0.5b_llamafac_500k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ahmedheakl/
qwen2.5_0.5b_llamafac_500k