fine_tuned_per_domain_balanced

This model is a fine-tuned version of Qwen/Qwen2-1.5B on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1209
• Accuracy: 0.9540

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• 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: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5664	0.0203	100	0.2706	0.8890
0.2871	0.0406	200	0.2891	0.8871
0.2495	0.0608	300	0.2310	0.9026
0.2414	0.0811	400	0.1710	0.9290
0.1983	0.1014	500	0.1614	0.9332
0.198	0.1217	600	0.1482	0.9394
0.2112	0.1419	700	0.1545	0.9443
0.1791	0.1622	800	0.1303	0.9501
0.1707	0.1825	900	0.1822	0.9340
0.1663	0.2028	1000	0.1297	0.9511
0.1657	0.2230	1100	0.1433	0.9492
0.1467	0.2433	1200	0.1107	0.9590
0.1519	0.2636	1300	0.1250	0.9548
0.1474	0.2839	1400	0.1045	0.9613
0.1509	0.3041	1500	0.1180	0.9593
0.147	0.3244	1600	0.1076	0.9588
0.1308	0.3447	1700	0.1209	0.9540

Framework versions

• Transformers 4.49.0
• Pytorch 2.6.0+cu126
• Datasets 3.3.2
• Tokenizers 0.21.0