This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct on the reranker_continuous_filt_max7_train dataset. It achieves the following results on the evaluation set:

Loss: 0.3869

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
0.403	0.1000	1977	0.4783
0.5192	0.2000	3954	0.4524
0.3639	0.3000	5931	0.4370
0.4343	0.4000	7908	0.4286
0.3929	0.5000	9885	0.4163
0.4455	0.6000	11862	0.4040
0.3775	0.7000	13839	0.3947
0.3629	0.8000	15816	0.3898
0.5186	0.9000	17793	0.3872

Framework versions

Transformers 4.46.1
Pytorch 2.4.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3

lightblue/reranker_0.5_cont_filt_7max

reranker_continuous_filt_max7_train

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lightblue/
reranker_0.5_cont_filt_7max