This model is a fine-tuned version of Qwen/Qwen2.5-Coder-1.5B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8436

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: 0.0002
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.9442	0.3556	100	0.8743
0.8925	0.7111	200	0.8538
0.8768	1.064	300	0.8480
0.8486	1.4196	400	0.8413
0.8312	1.7751	500	0.8365
0.7822	2.128	600	0.8438
0.7656	2.4836	700	0.8435
0.7807	2.8391	800	0.8436

Framework versions

PEFT 0.18.0
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1

zeynepelif/results_diverse

results_diverse

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

zeynepelif/
results_diverse