SLM_LAW

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

• Loss: 1.1380

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: 0.0005
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• 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_steps: 1000
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss
1.5039	0.0248	500	1.4864
1.4341	0.0496	1000	1.4603
1.3489	0.0744	1500	1.3271
1.2564	0.0992	2000	1.2632
1.2071	0.1240	2500	1.2287
1.1771	0.1488	3000	1.2031
1.1565	0.1737	3500	1.1845
1.1338	0.1985	4000	1.1688
1.1158	0.2233	4500	1.1507
1.0999	0.2481	5000	1.1380

Framework versions

• Transformers 4.52.0.dev0
• Pytorch 2.6.0+cu124
• Datasets 3.4.1
• Tokenizers 0.21.0