build_your_circuit_lora

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.9179

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: 8
• eval_batch_size: 8
• 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: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
5.6558	0.5263	500	2.7776
2.7422	1.0526	1000	1.9060
2.1288	1.5789	1500	1.6338
1.863	2.1053	2000	1.4802
1.6722	2.6316	2500	1.3769
1.5777	3.1579	3000	1.2927
1.4825	3.6842	3500	1.2269
1.43	4.2105	4000	1.1850
1.3737	4.7368	4500	1.1518
1.323	5.2632	5000	1.1274
1.2881	5.7895	5500	1.0999
1.2751	6.3158	6000	1.0804
1.2417	6.8421	6500	1.0641
1.2058	7.3684	7000	1.0429
1.1967	7.8947	7500	1.0309
1.1881	8.4211	8000	1.0186
1.1615	8.9474	8500	1.0139
1.1486	9.4737	9000	0.9940
1.139	10.0	9500	0.9825
1.1334	10.5263	10000	0.9786
1.1079	11.0526	10500	0.9731
1.1141	11.5789	11000	0.9648
1.1053	12.1053	11500	0.9613
1.0943	12.6316	12000	0.9539
1.0776	13.1579	12500	0.9502
1.1101	13.6842	13000	0.9415
1.0635	14.2105	13500	0.9373
1.0527	14.7368	14000	0.9371
1.0926	15.2632	14500	0.9317
1.0639	15.7895	15000	0.9310
1.0445	16.3158	15500	0.9272
1.0672	16.8421	16000	0.9260
1.0519	17.3684	16500	0.9227
1.0581	17.8947	17000	0.9203
1.0365	18.4211	17500	0.9193
1.0595	18.9474	18000	0.9178
1.0449	19.4737	18500	0.9179
1.0478	20.0	19000	0.9179

Framework versions

• PEFT 0.15.2
• Transformers 4.55.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.2