trained_model

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

• Loss: 0.5403
• Bertscore Precision: 0.9330
• Bertscore Recall: 0.9366
• Bertscore F1: 0.9348

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Bertscore Precision	Bertscore Recall	Bertscore F1
No log	0.9664	18	1.0760	0.8860	0.8931	0.8895
1.6935	1.9866	37	0.6704	0.9215	0.9234	0.9224
1.6935	2.9530	55	0.5852	0.9287	0.9322	0.9304
0.5756	3.9732	74	0.5481	0.9346	0.9373	0.9359
0.4437	4.8322	90	0.5403	0.9330	0.9366	0.9348

Framework versions

• PEFT 0.13.0
• Transformers 4.45.1
• Pytorch 2.5.1+cpu
• Datasets 3.0.1
• Tokenizers 0.20.0