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

Loss: 0.0526

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
0.0517	0.1000	1937	0.0871
0.114	0.2001	3874	0.0835
0.1033	0.3001	5811	0.0735
0.0544	0.4001	7748	0.0663
0.1169	0.5001	9685	0.0623
0.05	0.6002	11622	0.0599
0.0951	0.7002	13559	0.0566
0.0497	0.8002	15496	0.0551
0.1002	0.9002	17433	0.0532

Framework versions

Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3

lightblue/reranker_0.5_bin_filt

reranker_binary_filt_train

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lightblue/
reranker_0.5_bin_filt