QSolver_Encoder_V15

This model is a fine-tuned version of dahaludba/QSolver_Encoder_V13 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4253
• Map@3: 0.7256

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: 1.5e-05
• train_batch_size: 8
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Map@3
4.6756	0.9390	100	2.3653	0.7017
2.7995	1.8732	200	1.4014	0.8661
2.1169	2.8075	300	1.4253	0.7256

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 5.0.0
• Tokenizers 0.22.2