rsinema/Qwen2.5-0.5B-Instruct-dm

results

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

• Loss: 0.0422

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: 5e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.1222	0.2603	500	0.1168
0.0751	0.5206	1000	0.0764
0.0692	0.7808	1500	0.0636
0.043	1.0411	2000	0.0551
0.0439	1.3014	2500	0.0497
0.0411	1.5617	3000	0.0465
0.0373	1.8220	3500	0.0422

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1