lightblue/reranker_0.5_cont

reranker_continuous_train

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

• Loss: 0.3195

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 8
• total_eval_batch_size: 8
• optimizer: Use 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_ratio: 0.01
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.4242	0.1	2156	0.3844
0.236	0.2	4312	0.3643
0.6602	0.3	6468	0.3521
0.3464	0.4	8624	0.3472
0.3598	0.5	10780	0.3412
0.3377	0.6	12936	0.3341
0.4547	0.7	15092	0.3258
0.2282	0.8	17248	0.3228
0.2692	0.9	19404	0.3195
0.2059	1.0	21560	0.3195

Framework versions

• Transformers 4.46.1
• Pytorch 2.4.0+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3