lightblue/reranker_0.5_cont_filt

reranker_continuous_filt_train

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

• Loss: 0.2805

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
0.2895	0.1000	2016	0.3479
0.2891	0.2000	4032	0.3320
0.396	0.3000	6048	0.3245
0.2693	0.4000	8064	0.3080
0.2712	0.5000	10080	0.3056
0.2738	0.6000	12096	0.2925
0.1629	0.7000	14112	0.2880
0.2761	0.8000	16128	0.2839
0.1861	0.9000	18144	0.2813

Framework versions

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